{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ensemble Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_Last revision: Fri Jul 19 18:47:59 AEST 2019_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this short lab we will go into some \"hands-on\" aspects of ensemble learning, covering aspects of the bias-variance decomposition, random forests (bagged decision trees with random subspaces) and boosting algorithms discussed in lectures. The lab is in the form of a walk-though with questions you should try to answer for yourself before reading through the solutions. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Acknowledgement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*This notebook contains several excerpts from the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas (one of the original sklearn developers); the original content is available [on GitHub](https://github.com/jakevdp/PythonDataScienceHandbook).* \n",
    "\n",
    "*The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!*\n",
    "\n",
    "*The boosting example is modified from code from Chapter 13 of Machine Learning: An Algorithmic Perspective (2nd Edition) by Stephen Marsland (http://stephenmonika.net)*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As with previous labs, the objective is to expose some of the methods and to show some visualizations, since although some of the methods appear quite complex, many of the underlying ideas are quite straightforward. We will use the ``Seaborn`` visualization package which builds on and extends the capabilities of the standard ``Matplotlib`` package. *You will need to install these if you want to run this notebook locally.*\n",
    "\n",
    "You will also need to ensure the file ```helpers_ensembles.py``` in the folder or directory you run this notebook from."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from ipywidgets import interact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bias-Variance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Recall the usual setting: suppose we train a model on some data, then test on some data _not_ used for training, and we evaluate the observed test error as an estimate of the _generalization error_ of the model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** how could *bias* be observed in the estimation of error for a learned model? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer:** bias can be measured by calculating the magnitude of the error, the larger the error is, the larger the bias is"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** how could *variance* be observed in the estimation of error for a learned model?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer:**  variance measures the distribution of bias, larger variance means bias is more widely spread"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Think of how you would answer these questions before proceeding."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To answer these questions we will attempt firstly to visualize learning outcomes where the effect of bias and variance on error are clearly evident."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bias-Variance Tradeoff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll start by using regression for this visualization, and compare linear to non-linear models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "def PolynomialRegression(degree=2, **kwargs):\n",
    "    #pipline:process in (key1,value1),(key2,value2) order\n",
    "    #PolynomialFeatures: create n-degreee data: input is 2D [a,b], then the PolynomialFeatures is [1,ab,a2,b2,a,b]\n",
    "    return make_pipeline(PolynomialFeatures(degree),\n",
    "                         LinearRegression(**kwargs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next let's generate some data, and fit the models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_data(N=30, err=0.8, rseed=1):\n",
    "    # randomly sample the data\n",
    "    rng = np.random.RandomState(rseed)\n",
    "    X = rng.rand(N, 1) ** 2\n",
    "    y = 10 - 1. / (X.ravel() + 0.1)\n",
    "    if err > 0:\n",
    "        y += err * rng.randn(N)\n",
    "    return X, y\n",
    "\n",
    "X, y = make_data()\n",
    "xfit = np.linspace(-0.1, 1.0, 1000)[:, None]\n",
    "model1 = PolynomialRegression(1).fit(X, y)\n",
    "model20 = PolynomialRegression(20).fit(X, y)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
    "fig.subplots_adjust(left=0.0625, right=0.95, wspace=0.1)\n",
    "\n",
    "ax[0].scatter(X.ravel(), y, s=40)\n",
    "ax[0].plot(xfit.ravel(), model1.predict(xfit), color='gray')\n",
    "ax[0].axis([-0.1, 1.0, -2, 14])\n",
    "ax[0].set_title('High-bias model: Underfits the data', size=14)\n",
    "\n",
    "ax[1].scatter(X.ravel(), y, s=40)\n",
    "ax[1].plot(xfit.ravel(), model20.predict(xfit), color='gray')\n",
    "ax[1].axis([-0.1, 1.0, -2, 14])\n",
    "ax[1].set_title('High-variance model: Overfits the data', size=14);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at these plots can tell us something about the error. The first plot shows a linear model. Since the data appears to be non-linear, the error will have a considerable *bias* component, since the model can never fit all the data points. In the second plot the polynomial regression appears to have fit the data almost completely. However, the error of this model will have a considerable *variance* component due to the complexity of the fitted polynomial. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bias-Variance Tradeoff Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
    "fig.subplots_adjust(left=0.0625, right=0.95, wspace=0.1)\n",
    "\n",
    "X2, y2 = make_data(10, rseed=42)\n",
    "\n",
    "ax[0].scatter(X.ravel(), y, s=40, c='blue')\n",
    "ax[0].plot(xfit.ravel(), model1.predict(xfit), color='gray')\n",
    "ax[0].axis([-0.1, 1.0, -2, 14])\n",
    "ax[0].set_title('High-bias model: Underfits the data', size=14)\n",
    "ax[0].scatter(X2.ravel(), y2, s=40, c='red')\n",
    "ax[0].text(0.02, 0.98, \"training score: $R^2$ = {0:.2f}\".format(model1.score(X, y)),\n",
    "           ha='left', va='top', transform=ax[0].transAxes, size=14, color='blue')\n",
    "ax[0].text(0.02, 0.91, \"validation score: $R^2$ = {0:.2f}\".format(model1.score(X2, y2)),\n",
    "           ha='left', va='top', transform=ax[0].transAxes, size=14, color='red')\n",
    "\n",
    "ax[1].scatter(X.ravel(), y, s=40, c='blue')\n",
    "ax[1].plot(xfit.ravel(), model20.predict(xfit), color='gray')\n",
    "ax[1].axis([-0.1, 1.0, -2, 14])\n",
    "ax[1].set_title('High-variance model: Overfits the data', size=14)\n",
    "ax[1].scatter(X2.ravel(), y2, s=40, c='red')\n",
    "ax[1].text(0.02, 0.98, \"training score: $R^2$ = {0:.2g}\".format(model20.score(X, y)),\n",
    "           ha='left', va='top', transform=ax[1].transAxes, size=14, color='blue')\n",
    "ax[1].text(0.02, 0.91, \"validation score: $R^2$ = {0:.2g}\".format(model20.score(X2, y2)),\n",
    "           ha='left', va='top', transform=ax[1].transAxes, size=14, color='red');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The $R^2$ metric (coefficient of determination) is an estimate of how well a model fits a dataset. \n",
    "\n",
    "For the linear regression model, goodness of fit is about the same on training set and validation set. This suggests variance of this model is not high. However, linear regression does not fit the training set as well as polynomial regression, suggesting bias of the linear model is too high. On the other hand, polynomial regression does not fit the validation set well, suggesting the variance of this model is too high."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Validation Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 1, 1000)\n",
    "y1 = -(x - 0.5) ** 2\n",
    "y2 = y1 - 0.33 + np.exp(x - 1)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x, y2, lw=10, alpha=0.5, color='blue')\n",
    "ax.plot(x, y1, lw=10, alpha=0.5, color='red')\n",
    "\n",
    "ax.text(0.15, 0.2, \"training score\", rotation=45, size=16, color='blue')\n",
    "ax.text(0.2, -0.05, \"validation score\", rotation=20, size=16, color='red')\n",
    "\n",
    "ax.text(0.02, 0.1, r'$\\longleftarrow$ High Bias', size=18, rotation=90, va='center')\n",
    "ax.text(0.98, 0.1, r'$\\longleftarrow$ High Variance $\\longrightarrow$', size=18, rotation=90, ha='right', va='center')\n",
    "ax.text(0.48, -0.12, 'Best$\\\\longrightarrow$\\nModel', size=18, rotation=90, va='center')\n",
    "\n",
    "ax.set_xlim(0, 1)\n",
    "ax.set_ylim(-0.3, 0.5)\n",
    "\n",
    "ax.set_xlabel(r'model complexity $\\longrightarrow$', size=14)\n",
    "ax.set_ylabel(r'model score $\\longrightarrow$', size=14)\n",
    "\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.yaxis.set_major_formatter(plt.NullFormatter())\n",
    "\n",
    "ax.set_title(\"Validation Curve Schematic\", size=16);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This plot shows the trade-off of model complexity and model performance using a scoring metric for both training set and validation (off-training-set) data. The falling off in validation score reflects overfitting of the training set."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Learning Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "N = np.linspace(0, 1, 1000)\n",
    "y1 = 0.75 + 0.2 * np.exp(-4 * N)\n",
    "y2 = 0.7 - 0.6 * np.exp(-4 * N)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x, y1, lw=10, alpha=0.5, color='blue')\n",
    "ax.plot(x, y2, lw=10, alpha=0.5, color='red')\n",
    "\n",
    "ax.text(0.2, 0.88, \"training score\", rotation=-10, size=16, color='blue')\n",
    "ax.text(0.2, 0.5, \"validation score\", rotation=30, size=16, color='red')\n",
    "\n",
    "ax.text(0.98, 0.45, r'Good Fit $\\longrightarrow$', size=18, rotation=90, ha='right', va='center')\n",
    "ax.text(0.02, 0.57, r'$\\longleftarrow$ High Variance $\\longrightarrow$', size=18, rotation=90, va='center')\n",
    "\n",
    "ax.set_xlim(0, 1)\n",
    "ax.set_ylim(0, 1)\n",
    "\n",
    "ax.set_xlabel(r'training set size $\\longrightarrow$', size=14)\n",
    "ax.set_ylabel(r'model score $\\longrightarrow$', size=14)\n",
    "\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.yaxis.set_major_formatter(plt.NullFormatter())\n",
    "\n",
    "ax.set_title(\"Learning Curve Schematic\", size=16);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This plot shows the effect of increasing the sample size of data used in learning – \"big data\" can enable complex models to be learned without overfitting the training set."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bias-Variance in Validation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now summarise what we have visualized as follows:\n",
    "\n",
    "a <span style=\"color:red\">high bias</span> learner will *tend to* <span style=\"color:red\">under</span>fit\n",
    "\n",
    "a <span style=\"color:red\">high variance</span> learner will *tend to* <span style=\"color:red\">over</span>fit\n",
    "\n",
    "Although can only be a general guideline, it gives us at least a partial answer to the questions we asked above of how we can detect bias and variance when attempting to validate machine learning methods in terms of their error.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Decision Tree Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The bias-variance decomposition does not have the same mathematical derivation for classification as it does for regression with squared error. Nonetheless, we can still consider the role of a bias and a variance component in classification error.\n",
    "\n",
    "Here is an instance space which contains randomly generated examples centred in 4 regions of the 2D area. Each region represents a different class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.datasets import make_blobs\n",
    "from helpers_ensembles import visualize_tree\n",
    "\n",
    "X, y = make_blobs(n_samples=300, centers=4,\n",
    "                  random_state=0, cluster_std=1.0)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='rainbow');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Decision Tree Levels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is an example of learning a decision tree at successive depths of refinement, where at each depth a further refinement of the tree is applied to the instance space. At each depth, the decision tree gives a finer partition of the instance space, resulting in a lower-error classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 4, figsize=(16, 3))\n",
    "fig.subplots_adjust(left=0.02, right=0.98, wspace=0.1)\n",
    "\n",
    "for axi, depth in zip(ax, range(1, 5)):\n",
    "    model = DecisionTreeClassifier(max_depth=depth)\n",
    "    visualize_tree(model, X, y, ax=axi)\n",
    "    axi.set_title('depth = {0}'.format(depth))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Decision Tree Overfitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** What kind of problem do you think decision tree is likely to have when the depth goes deeper?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer:** decision tree is likely to overfit the model, the deper the tree, the higher the possiblity of overfitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One way to see the effect of this is to look at models trained on different subsets of the data—for example, in this figure we train two different trees, each on half of the original data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = DecisionTreeClassifier()\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
    "fig.subplots_adjust(left=0.0625, right=0.95, wspace=0.1)\n",
    "#m::n,starting from mth element, get every nth element\n",
    "visualize_tree(model, X[::2], y[::2], boundaries=False, ax=ax[0])\n",
    "visualize_tree(model, X[1::2], y[1::2], boundaries=False, ax=ax[1]);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** What do you think is going on in this visualization? What do you think can be done to improve this result?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer:** 1.same model does not generalized well on different datasets 2. overfitting, sensitive to outliers I think it is possible to do pruning or make the tree less deeper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ensembles of Estimators: Random Forests\n",
    "\n",
    "**Question:** What could we do to make use of multiple overfitting estimators to reduce the effect of overfitting?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer:**We can ensemble some of the overfitting estimators together, and assign each a subst of the whole dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's write a quick utility function to help us visualize the output of a classifier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualize_classifier(model, X, y, ax=None, cmap='rainbow'):\n",
    "    ax = ax or plt.gca()#get current axis\n",
    "    \n",
    "    # Plot the training points\n",
    "    ax.scatter(X[:, 0], X[:, 1], c=y, s=30, cmap=cmap,\n",
    "                        clim=(y.min(), y.max()), zorder=3)\n",
    "    ax.axis('tight')\n",
    "    ax.axis('off')\n",
    "    xlim = ax.get_xlim()\n",
    "    ylim = ax.get_ylim()\n",
    "    \n",
    "    # fit the estimator\n",
    "    model.fit(X, y)\n",
    "    xx, yy = np.meshgrid(np.linspace(*xlim, num=200),\n",
    "                         np.linspace(*ylim, num=200))\n",
    "    Z = model.predict(np.c_[xx.ravel(), yy.ravel()]).reshape(xx.shape)\n",
    "\n",
    "    # Create a color plot with the results\n",
    "    n_classes = len(np.unique(y))\n",
    "    contours = ax.contourf(xx, yy, Z, alpha=0.3,\n",
    "                           levels=np.arange(n_classes + 1) - 0.5,\n",
    "                           cmap=cmap, zorder=1)\n",
    "\n",
    "    ax.set(xlim=xlim, ylim=ylim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This type of bagging classification can be done manually using Scikit-Learn's ``BaggingClassifier`` meta-estimator, as shown here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_blobs\n",
    "\n",
    "X, y = make_blobs(n_samples=300, centers=4,random_state=0, cluster_std=0.7)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='rainbow');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "\n",
    "tree = DecisionTreeClassifier()\n",
    "bag = BaggingClassifier(tree, n_estimators=100, max_samples=0.8,random_state=1)#n_estimators = number of trees\n",
    "\n",
    "bag.fit(X, y)\n",
    "visualize_classifier(bag, X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we have randomized the data by fitting each estimator with a random subset of 80% of the training points.\n",
    "In practice, decision trees are more effectively randomized by injecting some stochasticity in how the splits are chosen: this way all the data contributes to the fit each time, but the results of the fit still have the desired randomness.\n",
    "For example, when determining which feature to split on, the randomized tree might select from among the top several features.\n",
    "You can read more technical details about these randomization strategies in the [Scikit-Learn documentation](http://scikit-learn.org/stable/modules/ensemble.html#forest) and references within.\n",
    "\n",
    "In Scikit-Learn, such an optimized ensemble of randomized decision trees is implemented in the ``RandomForestClassifier`` estimator, which takes care of all the randomization automatically.\n",
    "All you need to do is select a number of estimators, and it will very quickly (in parallel, if desired) fit the ensemble of trees:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "model = RandomForestClassifier(n_estimators=100, random_state=0)\n",
    "visualize_classifier(model, X, y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that by averaging over 100 randomly perturbed models, we end up with an overall model that is much closer to our intuition about how the parameter space should be split."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Forest Regression\n",
    "\n",
    "In the previous section we considered random forests within the context of classification.\n",
    "Random forests can also be made to work in the case of regression (that is, continuous rather than categorical variables). The estimator to use for this is the ``RandomForestRegressor``, and the syntax is very similar to what we saw earlier.\n",
    "\n",
    "Consider the following data, drawn from the combination of a fast and slow oscillation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = np.random.RandomState(42)\n",
    "x = 10 * rng.rand(200)\n",
    "\n",
    "def model(x, sigma=0.3):\n",
    "    fast_oscillation = np.sin(5 * x)\n",
    "    slow_oscillation = np.sin(0.5 * x)\n",
    "    noise = sigma * rng.randn(len(x))\n",
    "    return slow_oscillation + fast_oscillation + noise\n",
    "\n",
    "y = model(x)\n",
    "plt.errorbar(x, y, 0.3, fmt='o');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the random forest regressor, we can find the best fit curve as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200,)\n",
      "(200,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "forest = RandomForestRegressor(200)\n",
    "print(x.shape)\n",
    "print(y.shape)\n",
    "forest.fit(x[:, None], y)\n",
    "\n",
    "xfit = np.linspace(0, 10, 1000)\n",
    "yfit = forest.predict(xfit[:, None])\n",
    "ytrue = model(xfit, sigma=0)\n",
    "\n",
    "plt.errorbar(x, y, 0.3, fmt='o', alpha=0.5)\n",
    "plt.plot(xfit, yfit, '-r');\n",
    "plt.plot(xfit, ytrue, '-k', alpha=0.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here the true model is shown in the smooth gray curve, while the random forest model is shown by the jagged red curve. As you can see, the non-parametric random forest model is flexible enough to fit the multi-period data, without us needing to specifying a multi-period model!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Random Forest for Classifying Digits\n",
    "\n",
    "We previously looked at the hand-written digits data, and we use that again here to see how the random forest classifier can be used in this context."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data', 'target', 'target_names', 'images', 'DESCR'])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "digits = load_digits()\n",
    "digits.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To remind us what we're looking at, we'll visualize the first few data points:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TxjxQ5d96WNlqIqX9A3JpKu34DfRWE01paWnQfaycZ7dYmVdS2bOB3pKhvT+lOaJtW5DmorYlQCsB5xbpOGvvGak0nzbfpONrpcxiD22rinTOtD7SsXBrC9Ot8JMiERGRgYsiERGRgYsiERGRgYsiERGRgYsiERGRwfXsU6nAc0ZGhthHyo7UspHcyPiz8pxaVpeVGxO7wUpWl5VC3V5kj2nHUspy04p7DxZaxrCU2acdf+35BjsrmZNatrNb2cLSTYEBYMeOHabt2o2hpTi/++47sY+bRc3NWCmgL8Xo1RzlJ0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiKD61syrGw3OHTokGl7Y2Oj2MeNtGotpT0tLc20fcyYMWIfqfC0li4upSXbGe9gKsbtNC2NW3ps2rRpYh8plXygU9218y0VwdZI49Ler14VaL6ZttVBOi9aoXM7xbE1VrYUaMXOtXFLtK1vVmnH0sp1qbi42EY0zuMnRSIiIgMXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIoMj2adaNuPChQtN2zds2CD2kbK2pILagJxB5laxX2nM2rGwkrEoZXrZyZizEodWdFjKWNSOhZWMyf7QxvbRRx+ZtldVVYl9pDnndJagHdIc12KMiooybR8sGaYa7T0tzTkr8yInJyeIqP6eNsel94z2vpbeg1r29GOPPSY+ZpU2R6QbB2jvMYnT19L+4idFIiIiAxdFIiIiAxdFIiIiAxdFIiIiAxdFIiIiAxdFIiIigyNbMrQUaSn1WysqK23J0IrbSunnbqX+S7RUYWnMWuq8G8WKtZTq7Oxs0/by8nKxz3vvvRf06wx0QW2NNEc1g2nrgjSvKioqxD5W3pfSmKU0/P7QCpBLNwa4dOmS2EfaDqNtKbJSuLs/tDkivee14yHdbMDu1pFgWTlnRUVFYh/p5gpeXSP4SZGIiMjARZGIiMhge1EsLy/HPffcg3vuuQclJSW4fv26E3F5rqKiAqmpqUhJSRnwCiVu2rt3L5KSkpCYmIhNmzZ5HY5jVq9ejZiYGKSmpnodiqPOnTuHhQsXIjk5GSkpKepXokPJ9evXMXfuXMyfPx/33HMPNm7c6HVIjvL7/cjIyMDSpUu9DsVRcXFxuPfee3HfffeJ1cqGOluLYktLC1599VVUV1fjs88+w48//oh3333Xqdg8c/LkSbzxxhs4evQo6uvrsXv3bpw+fdrrsGzz+/1Yu3Yt9uzZg1OnTmHnzp04deqU12E5YtWqVdi7d6/XYTguPDwcmzdvxhdffIEjR45g69atIXHOhg8fjurqanzyySc4fPgwDhw4gP/+7//2OizHVFRUIDk52eswXPH+++/j448/xsGDB70OxRW2Pyl2d3fj+vXr6O7uRnt7OyZMmOBEXJ764osvMG/ePERGRiI8PBzZ2dliMslQcvToUSQmJiIhIQERERFYsWKFpZqEg9GCBQswduxYr8Nw3MSJE5GZmQkAGDVqFJKTk9HS0uJxVPb5fD6MHDkSANDV1YWuri74fD6Po3JGc3MzPvjgA6xZs8brUMgCW9mnkydPxvPPP4+ZM2dixIgRePDBB7F8+fIb/o6UGSVlUgFyZpxW3FbLmgtWamoq/vVf/xVtbW0YMWIEPvzwQ8yePbtfr6cVsZWytqSCxICzGVgtLS2YMmVK759jY2Px5z//+Ya/I2W7asdXGrOWVTuYaMdYyoyrr68X+0jn2W7GalNTE06cOIGsrKwb2qXsTy2rUhqzlu0sxW81+9Hv9+Pee+/F2bNn8Ytf/AKJiYk3HDst4zlY2rXDTvasmWeffRYvv/wyrl69aqmvRLouOh2/xufz4eGHHwYAPProo3j00UdveFzKMtWyf93IsLfD1ifFS5cuoaqqCo2Njfj6669x7do1vPXWW07F5pnk5GSsX78eubm5WLx4MdLS0hAe7sjuFU8FAoG/awuVf52Huu+//x75+fl45ZVXMHr0aK/DcURYWBg+/PBDfPbZZ6ivr0dDQ4PXIdm2e/duxMTEYNasWV6H4oqamhq8/vrreOmll/DHP/5R/cfhUGVrUdy/fz/i4+MRHR2NYcOGYfny5fj000+dis1TJSUlqK2txeHDhzF27FjccccdXodkW2xsLM6dO9f75+bmZkyaNMnDiKg/urq6kJ+fj5UrV/7dNzGhYPTo0Zg3b564x20oqampwa5duxAXF4cVK1aguroaTz31lNdhOabnejFmzBjcd999+Mtf/uJxRM6ztShOnToVR44cQXt7OwKBAA4cOBAyPy5fuHABAPDVV1/h3XffRWFhoccR2TdnzhycPn0ajY2N6OzsRGVlJZYtW+Z1WKQIBAIoKSlBcnIynnvuOa/DcczFixd7vyq9fv06PvnkE0yfPt3jqOzbuHEjmpub0dTUhMrKStx///0h8e0ZAFy7dq33K+GOjg4cO3YM8fHxHkflPFvfCWZlZaGgoACZmZkIDw9HRkYGnn76aadi81R+fj7a2towbNgwbN26Vf0NdKgIDw/Ha6+9hoceegh+vx+rV69GSkqK12E5orCwEB999BFaW1sRGxuLsrIylJSUeB2WbTU1NXjzzTcxc+bM3t8BX3zxRSxZssTjyOz55ptvUFRUhI6ODgQCATzyyCN44IEHvA6LFOfPn0deXh6+//57+P1+LFq0CHPnzvU6LMfZ/qGsrKwMZWVlTsQyqHz88cdeh+CKJUuWDPkLqpmdO3d6HYIr5s+fb/pb8FB3991348SJE66VWBsMcnJyBrwEm5sSEhJQX1+vJgaGAla0ISIiMviC+Veoz+e7COCse+EMqGmBQCAaCLlxAcbYQnVcQMids1AdF8C5ONSE6riAPmPTBLUoEhERhTJ+fUpERGQIKtFm3LhxAe3eicH4+uuvxcd6tkPcbObMmWKfsLCwoF6/qakJra2tPsDauPx+v2n7+fPnxT7SuLRKJ1aO9/Hjx1sDgUC0lXFJiQ8jRowQ+7S1tZm2jxo1SuzTt7JOf/WMC7B2zqQ4tbkovYY2tmDZnYvt7e3i80oiIiJM27VxjR8/Pqi4AHtzUdLZ2Sk+9vnnnwf9fNJ1RTpGgP25KM25b775RuwjbVlx8t6e/ZmL0rUPAL799lvT9itXroh9pPmrXdMTEhJM27XCFn3PmSaoRTEuLg7Hjh0LpotIu/mvdFcKrQBtsBOjb9k2K+OSSnlpd9SQHtMq6Vsplebz+c4C1sYllYzSSqFJMWqZd1buPNIzLsDa2KzciHrbtm2m7U5mFdqdi1KZPa38l3QR18ZlpZSinbko0RZ7K/vmdu3aZdquLXR256I057RM/s2bN5u2ayXsgtWfuajd5Pmll14ybd+3b5/Yp7a21rRd+wfav/3bv5m2L1q0SOzT95xp+PUpERGRgYsiERGRgYsiERGRgYsiERGRwbP7IWmlgqSkGSezrPpDuzeilXvYSfEPprJJUozasZD6aElCUtKGUxmKZqT7tp09K//+biWJaKBJSRvabX2kx7SbTj/++OOm7W6eMzNDpTSclIwHyHNRS5qRjv9A7zU/c+aM+Njx48dN23Nzc8U+0mNacs769euDev1g8JMiERGRgYsiERGRgYsiERGRgYsiERGRgYsiERGRgYsiERGRwfUtGVIq/6FDh8Q+5eXlboUTFC1VX6oF6vQ2joEmpX1rtUqllHynC53bZeWc7dixw7Rdq5fqxti0bTvSNorS0lKxjxS/VuPWDdq2Bem8aMdekp2dLT7m1lzU5r90nLVtTFbmrxvnc9asWeJj2jYKibTF4/e//73Y55lnngn6dfqLnxSJiIgMXBSJiIgMXBSJiIgMXBSJiIgMXBSJiIgMnmWfaqQMyIGmFeedNm2aabtWUFkqAqyNV8pMdStjTspW08ZVVFRk2q5l0nlBKkKuZXZKx1m7C710ngealjEs0TKu3aDNkXXr1g1cIANMmj9aNq5UxN2LTO5gaUXEp0+fbtqemZkp9nn66adtxyThJ0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiKD61sytBRjSXx8vGl7Wlqa2KesrMy0XdtWYUdGRoZjzyUVnQbkLRnaNgI7pO0h2rGXCp1rBZG9IMVj5Vhq22ikbUh2ijPn5OQE3Ud770nHQiucLW2fsFKgu4e2tUUas7bVRHovDaai+4A8F7TjIZ2bwfY+M5OQkCA+Jl3vf/3rX4t9xowZYzsmCT8pEhERGbgoEhERGbgoEhERGbgoEhERGbgoEhERGVzPPrWSmVZaWupYHzvZp1r23oYNG0zbtUxGKQNOyt4EBk9xdG1cUoxuZcgOBsXFxeJj0px3q1B4VFRUUHEAcganNucHuvC0lKFpJY7BVjRbylDWCqRrWepDWW5urmn7+vXrxT5PPPGEW+HwkyIREVEPLopEREQGLopEREQGLopEREQGLopEREQGLopEREQG17dkSGn5VrYaaMVyKyoqTNulbRCdnZ23fD2t0K6U7q5tr5DS3e0UVLbCStq91mewFVuWSGOQ0uM1jY2N4mNVVVWm7Xbmokaac1a2gGjnebBsD7KyveLQoUPiY9J5cXMbh5VjeeLEiaDatdexU5xe89JLL5m2X7p0Sezz+9//3rTdys0knMBPikRERAbbi+Lly5dRUFCAGTNmIDk5GZ999pkTcXmqoaEB6enpvf+NHj1avV3NUFJeXo577rkH99xzD0pKSnD9+nWvQ3JMRUUFUlNTkZKSEjLnCwD27t2LpKQkJCYmYtOmTV6H45jVq1cjJiYGqampXofiqHPnzmHhwoVITk5GSkqK+C3WUHP9+nXMnTsXaWlpSElJEQuYDHW2F8XS0lIsXrwYf/nLX1BfX4/k5GQn4vJUUlIS6urqUFdXh+PHjyMyMhJ5eXleh2VbS0sLXn31VVRXV+Ozzz7Djz/+iHfffdfrsBxx8uRJvPHGGzh69Cjq6+uxe/dunD592uuwbPP7/Vi7di327NmDU6dOYefOnTh16pTXYTli1apV2Lt3r9dhOC48PBybN2/GF198gSNHjmDr1q0hcc6GDx+O6upq1NfXo66uDnv37sWRI0e8DstxthbFK1eu4PDhwygpKQEAREREDIkbXgbjwIEDmD59OqZNm+Z1KI7o7u7G9evX0d3djfb2dkyYMMHrkBzxxRdfYN68eYiMjER4eDiys7Px3nvveR2WbUePHkViYiISEhIQERGBFStWiL9ZDjULFizA2LFjvQ7DcRMnTkRmZiYAYNSoUUhOTkZLS4vHUdnn8/kwcuRIAEBXVxe6urrg8/k8jsp5thbFM2fOIDo6GsXFxcjIyMCaNWtw7do1p2IbFCorK1FYWOh1GI6YPHkynn/+ecycORMzZszA6NGjcf/993sdliNSU1Nx+PBhtLW1ob29HR9++CHOnTvndVi2tbS0YMqUKb1/jo2NDYkL7D+KpqYmnDhxAllZWV6H4gi/34/09HTExMQgNzc3ZMbVl63s0+7ubtTW1mLLli3IyspCaWkpNm3ahBdeeKH370hZTlomqZSNqX03LxX+ljLIIiIixOfq0dnZiV27dmHjxo23/Ls9tIypnJycfj+PGy5duoSqqio0NjbitttuwxNPPIHdu3fjqaee6v07Uvxa7IPhN5Pk5GSsX78eubm5GDlyJNLS0hAefuP0lootr1u3LujXS0tLEx+T5qL0LUpYWJj4XIFA4O/abv7XufRe0rJqpaxwrSD1YPkWSJuL2dnZpu3asXAr+/T7779Hfn4+XnnlFYwePfqGx6RzpmUMWymwLz2f9Fx+v199vrCwMNTV1eHy5cvIy8vDyZMnb/hNWPrNW7suLlq0yLR927ZtaixusfVJMTY2FrGxsb3/WigoKEBtba0jgQ0Ge/bsQWZmJsaPH+91KI7Yv38/4uPjER0djWHDhmH58uX49NNPvQ7LMSUlJaitrcXhw4cxduxY3HHHHV6HZFtsbOwNn3ibm5sxadIkDyOi/ujq6kJ+fj5WrlyJ5cuXex2O42677Tbk5OSE5G/CthbFCRMmYMqUKWhoaADwt9/f7rrrLkcCGwx27twZMl+dAsDUqVNx5MgRtLe3IxAI4MCBAyGRGNXjwoULAICvvvoFNfZtAAAgAElEQVQK7777bkicuzlz5uD06dNobGxEZ2cnKisrsWzZMq/DIkUgEEBJSQmSk5Px3HPPeR2OYy5evNj7ia+jowP79+/HjBkzPI7KebY372/ZsgUrV65EZ2cnEhISsH37difi8lx7ezv27dvn2Ud4N2RlZaGgoACZmZkIDw9HRkYGnn76aa/Dckx+fj7a2towbNgwbN26FWPGjPE6JNvCw8Px2muv4aGHHoLf78fq1auRkpLidViOKCwsxEcffYTW1lbExsairKysN2lvKKupqcGbb76JmTNn9v589OKLL2LJkiUeR2bPN998g6KiIvj9fvz444948sknsXTpUq/DcpztRTE9PR3Hjh1zIpZBJTIyEm1tbV6H4biysjKUlZV5HYYrPv74Y69DcMWSJUuG/AXVzM6dO70OwRXz5883/S14qLv77rvV6jmhghVtiIiIDFwUiYiIDL5gPub7fL6LAM66F86AmhYIBKKBkBsXYIwtVMcFhNw5C9VxAZyLQ02ojgvoMzZNUIsiERFRKAsq0WbcuHEBN2+n0qNni8fN4uPjxT792YzfV1NTE1pbW32AtXFJMY4aNSqo5wH0zdtW9kgeP368NRAIRFsZl7R5Vxqv1mf69Olin8jIyKDiAv5vXICzc/Hrr78WH7OSbJWUlGTaLs1Ru3NR2nze3d0t9pHmlZX5q7EzF6WKRFevXhX73H777abtTu81tjsXpXOmjW3EiBGm7dq+1WDfZ3bnonQbtC+//FLsIxWFcHo/bt9zpglqUYyLixuQTFOpYoVWbSPYkzd79uwb+gY7LilGK1VrtEohWuUfic/nOwtYG5eVijZSn7ffflvsY+V+bj3jApydi9r9LLU5J9m1a5dpuzRH7c5F6X6KWhURaV45XXXJzlyUYtQqu0jHwsr7SGN3LkpxamOT3jPa/A32fWZ3LkqLvXb/SOkxp+8z2/ecaZhoQ0REZOCiSEREZOCiSEREZOCiSEREZLBd5s0qLYFB+rF2oG9do91u5tChQ0G1A/Ithby+pVRfr7zyiml7fX292Ee6jdJgudXQrWhJWtK50W7xY+W2QG7Qkjak95iV53PrPEvvP20uSrcB0xI93Mqo147/jh07TNu1W5JJY9DGJh1Dt86ZNGbtnEmPaedFSlRyAj8pEhERGbgoEhERGbgoEhERGbgoEhERGbgoEhERGbgoEhERGVzfkiGl6BYXF4t9ysvLTdul7QKA83XyAD1tedq0aabt2jaOwbJFQUvHLysrC/r5pO01A1E83glaerf0mDa2gT7PUizaVh9pe4g2LmluD/SWIm3bgpTeb6Veqhe0bTvSudH6SO9Np2vB9hgzZoxpe1RUlNjHyri4JYOIiGgAcFEkIiIycFEkIiIycFEkIiIycFEkIiIyuJ59KmU5lZaWBt3H5/OJfaQMJjtZSloRW4mVguADTbsjuyQ7O1t8bDBlmWqZtVImnpYxLB2rs2flm3gP9PGQMq+1u65LGbJWiqO7RXrvapnrEi073a1MRi3jVWJl7mjZzvHx8UE/nx3SNU47/lIRdytF653AT4pEREQGLopEREQGLopEREQGLopEREQGLopEREQGLopEREQGR7ZkSKnugLytQUsXf/zxx4OOwY20aq3wsJSqr8UubUPRCp27QdtOINHSo6VtKF5sQdHmopVi51a4URBc20YjzX0rW4q07SkDTRqX9l6X5qm2NUEas3aNGkyGQrFzrQC59JiV4vROnDN+UiQiIjJwUSQiIjJwUSQiIjJwUSQiIjJwUSQiIjI4kn2qZTiNGTPGtP29994T+3hVCPZmWvaTlA2oxS5lwGmZWW4Ul542bVrQfbSMVSvZwtu3bzdtt5stpxUe1h6TSGMbTBl/UiwnTpwQ+0hZulrsWmbvYCG9X7QbEEjZ34NtvFaK0w+VDFoz2nVRei//8Y9/tP26/KRIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERkcGRLhkYqCq0Vi5ZSoYuLi50IyRFSGryWqi/RtnG4sSVDe05pu4aVIuIaK1sC3KKlfldVVZm2l5eXi33cKAiuPaf0mFbcWzr+VrbXuEWKX3uPSSn52ntMmttWtvD0lZOTIz4mFae3Uvg9KipK7OPGXLRCm4vSmLXtJOvWrTNtd2I7Hz8pEhERGWwvin6/HxkZGVi6dKkT8QwacXFxmDlzJtLT0zF79myvw3HM5cuXUVRUhLlz5yIrKwtHjx71OiRHNDQ0ID09vfe/0aNHD/gtudxSXl6OlJQUpKamorCwENevX/c6JEdUVFQgNTUVKSkpIXOuAGDv3r1ISkrCypUr8fbbb3sdjqNC9Zz1ZXtRrKioQHJyshOxDDoHDx5EXV0djh075nUojiktLcUDDzyAo0eP4uOPP0ZSUpLXITkiKSkJdXV1qKurw/HjxxEZGYm8vDyvw7KtpaUFr776Ko4dO4aTJ0/C7/ejsrLS67BsO3nyJN544w0cPXoU9fX12L17N06fPu11WLb5/X6sXbsWe/bswe9+9zscOHBg0FTositUz9nNbC2Kzc3N+OCDD7BmzRqn4iEXXblyBYcPH8YvfvELAEBERIT6e8RQdeDAAUyfPt1SObvBqLu7Gx0dHeju7kZ7ezsmTZrkdUi2ffHFF5g3bx4iIyMRHh6O7OxstfTjUHH06FEkJiYiISEBw4YNw/3334+amhqvw3JEqJ6zm9laFJ999lm8/PLL+MlPQu+nSZ/PhwcffBCzZs3C66+/7nU4jjhz5gyio6Oxdu1aLFiwAP/8z/+Ma9eueR2W4yorK1FYWOh1GI6YPHkynn/+eUydOhUTJ05EVFQUHnzwQa/Dsi01NRWHDx9GW1sb2tvb8eGHH+LcuXNeh2VbS0sLpkyZ0vvn6OhotLa2ehiRc0L1nN3Mcvbp7t27ERMTg1mzZlnKuNRImXEbNmxw9HU0NTU1mDRpEi5cuIDc3FzMmDEDCxYs6H1c+j5dy7KSihJrWWpO6u7uRm1tLbZs2YKsrCyUlpbit7/9LV544YXevyNl72kZmtKYtcw3t7IcOzs7sWvXLmzcuLHffbRzlpaWZto+UFmyly5dQlVVFRobG3HbbbfhiSeewFtvvYWnnnrqlrFYKY4+UONKTk7G+vXrkZubi5EjRyItLQ3h4TdejqTripWiz1rGtZTlaCXzOxAI9P5/Tk4Ozp07h6tXr/7de1zKvpduoAAA2dnZpu1OX38l/Tln0lfF2jVOOs5aJq70vnSC5Y94NTU12LVrF+Li4rBixQpUV1ff8EYd6nq+ooqJiUFeXl5IJKTExsYiNjYWWVlZAICCggLU1tZ6HJWz9uzZg8zMTIwfP97rUByxf/9+xMfHIzo6GsOGDcPy5cvx6aefeh2WI0pKSlBbW4vDhw9j7NixuOOOO7wOybbY2NgbPj01NzeHxNfdPULxnN3M8qK4ceNGNDc3o6mpCZWVlbj//vvx1ltvORmbZ65du4arV6/2/v+f/vQnpKamehyVfRMmTMCUKVPQ0NAA4G+/vd11110eR+WsnTt3hsxXpwAwdepUHDlyBO3t7QgEAjhw4EDIJLZduHABAPDVV1/h3XffDYnzNmfOHJw+fRqNjY3o7OxEZWUlli1b5nVYjgnFc3Yz1zfvD0Xnz5/vzVzs7u7Gz3/+cyxevNjjqJyxZcsWrFy5Ep2dnUhISBDvazgUtbe3Y9++fdi2bZvXoTgmKysLBQUFyMzMRHh4ODIyMvD00097HZYj8vPz0dbWhmHDhmHr1q3qV4dDRXh4OF577TU89NBD8Pv9WL16NVJSUrwOyzGheM5u5siimJOTM2C/iw2EhIQE1NfXex2GK9LT00Nqi0lfkZGRaGtr8zoMx5WVlYkVUIayjz/+2OsQXLFkyRIsWbLE6zBcEarnrK/QSxslIiKyiIsiERGRwdc3hfiWf9nnuwjA2crQ3pkWCASigZAbF2CMLVTHBYTcOQvVcQGci0NNqI4L6DM2TVCLIhERUSjj16dERESGoLJPx40bFzCrPtDZ2Sn2+fLLL03bOzo6gnnpW5JqeCYmJpq2NzU1obW11QfI49IyGc+fP2/arm3UbW9vFx+TSJvQw8LCxD7Hjx9vDQQC0dK4rNCqS0ilnrRi4xEREUHH0DMuQD5n2jH+61//atoeExMTdCzDhw8XH7v99tuDeq7+zEWNNE+//vprsc+oUaNM27X5a+ecWRnXqVOnTNsjIyPFPn1LrPWlvV+s6M9c1EjXD410nrVr6Z133mnaLp3//sxFv98vvp4053r2N5oZMWKEabv2PrJSnKPvOdMEtSjGxcWZpvNrVeClcl5Ob3mQtoRIJaH63g5KGpdUbg6Qy7xpqfMnTpwQH5NI5dW0Emo+n+8sII/LCulmu4Bcvm7Xrl1iHyuLdc+4evqbjU0r2SbNESv7/rT4gy2V1p+5qJHmqVbmTToWWh8758zKuKTya9rNZ6X3pdM32+3PXNRYue2SdJ61a6m0Z1c6//2Zi9o/kKX5U1FRIfaRFm7tfaSVnZT0PWcafn1KRERk4KJIRERk4KJIRERkcKTMm/adtvRYUVGR2Ee6Y7p2Q1ztdwartN9KpXE5fUsk6Xcct27xI/1eoN22y8lb79il/d7x3XffmbZbKaGm3bpG+r3GreNh5fcV6bdX7X0k3aLIzntP+61aeo9p51j63c3KMXKTlq8gkcagPZd0nu2U5dReT8rhOHjwYNDPp90izM3zyU+KREREBi6KREREBi6KREREBi6KREREBi6KREREBi6KREREBke2ZFy6dCnoPloa97Rp04Lu4wYrKfRSyTPA2tYFO6nTVhw6dMi0Xdt2o6VODzQr5by0cyalfg/0dhNte5C01UTb9iSlwWvvMamPlZJlPbRtVhJtO5IUy2DbkiEdZ21s0vHX5rwbW7e015O2y2jXiB07dpi2P/bYY8EF5hB+UiQiIjJwUSQiIjJwUSQiIjJwUSQiIjJwUSQiIjI4kn2q3dhVsm7duqD7bN++XXzMrQLZwdJupill2knZV16QMom1LEEpM9WLguBWsk+1cyZl/EnFsQF3sqStjEsqrG/1dRYuXBj0892KNkekLHQrBdy1ItZeXDukcWvHWMomHujsb+14SWuBlj1dXl5u2m4nq9kOflIkIiIycFEkIiIycFEkIiIycFEkIiIycFEkIiIycFEkIiIyOLIlQ0vRlVK8tULXVor6upFWrT2nlFItFWcG5JRqKSUZcKcorlS0F5CPsZVxaefYSnHj/tBS/KXjrL2mFKeW4u9GKrmV4yJtadBoc8NK4f9b0c6XlN6vbQGTtido5+Txxx83bbc7F7U4tfnjZJ+B5uTc/81vfiM+Jm3xcGIbGD8pEhERGbgoEhERGbgoEhERGbgoEhERGbgoEhERGRzJPtUKIEuPaVlu2mODhZRZqWWcSRmcbhSQ1mjHV8re0vpIY5ay+gA5s8zNIsBSZq02NinOgS52rsUoFWs/e/as2MdKEX/tfLrBSua69Jj2HpMyVu1mtGuFuqXn1s5LVVWVabsbGeqDgXaepYL8TuxC4CdFIiIiAxdFIiIiAxdFIiIiAxdFIiIiAxdFIiIiAxdFIiIigyNbMjRS6qxW3Lu+vt60ffv27U6E1G9aGry0dUBLw5ZS590oZq7RthNI41q4cKHYRypUPNi21kgp7aWlpWIfaQxasWI3aMWppa0+2vtFSv3X0uDtFsgOlnS+Tpw4IfbJyMgwbdfGJZ1Lu+9LKwXxtfemNO6B3pKhbRuRjpm2nUc6Z9rrFBcXi4/ZxU+KREREBtuLYlxcHGbOnIn09HTMnj3biZgGhbi4ONx7772477771E9JQ83ly5dRUFCAGTNmIDk5GZ999pnXITkmVOfi3r17kZSUhMTERGzatMnrcBxTUVGB1NRUpKSkuFq0YaCVl5cjJSUFxcXFeOGFF9DZ2el1SI6pqKhAQUEB8vPz8V//9V9eh+MKR74+PXjwIMaNG+fEUw0q77//Pm6//Xavw3BUaWkpFi9ejHfeeQednZ1ob2/3OiRHhdpc9Pv9WLt2Lfbt24fY2FjMmTMHy5Ytw1133eV1aLacPHkSb7zxBo4ePYqIiAgsXrwYjzzyCO644w6vQ7OlpaUFr776Kk6dOoU///nP+M1vfoPq6mosXrzY69Bs6zlnb775JoYNG4a1a9di/vz5lu7bOZjx69N/IFeuXMHhw4dRUlICAIiIiBjw34koOEePHkViYiISEhIQERGBFStWiL+1DSVffPEF5s2bh8jISISHhyM7Oxvvvfee12E5oru7Gx0dHfD7/fjhhx9C5h/WPedsxIgRCA8Px6xZs3Dw4EGvw3Kc7UXR5/PhwQcfxKxZs/D66687EdOg4PP5sHz5cuTk5AyJO173x5kzZxAdHY3i4mJkZGRgzZo1uHbtmtdhOSYU52JLSwumTJnS++fY2Fi0tLR4GJEzUlNTcfjwYbS1taG9vR0ffvghzp0753VYtk2ePBnPP/88pk6divz8fPz0pz/FnDlzvA7LET3n7PLly+jo6MAnn3yCb7/91uuwHGf769Oamhp0dnaitbUVv/jFLxAVFYWsrKzex6Xf46RMTADYsGGDaftAZmnW1NTgr3/9Ky5duoTnn38ePp8PaWlpvY+XlZWZ9tPGJWXiDlRB8O7ubtTW1mLLli3IyspCaWkpNm3ahBdeeKH370gZc1pWrZRZph0LN85lTU0NIiMjcfHiReTl5WHy5Mn4f//v//U+XlRUZNpP+7Tc1NQUdB8nBQKBv2vz+Xw3/Lm8vNy077p168TnlTIWB+q3veTkZKxfvx65ubkYOXIk0tLSEB5+4+VIug5opPilDF0AN7yv7bp06RKqqqrQ2NgI4G/zvKGhAT/72c9u+HtSVvOOHTvE5x7o7Pub9Zyz5557DiNHjsS9996LESNG3HD9kq4f2gcL6dqiZe9mZ2f3J2RLbH9SnDRpEgBg3LhxeOihh8TtFENNz7jGjBmD++67D3/5y188jsi+2NhYxMbG9v6jpaCgALW1tR5H5ZyecxYdHY2lS5eGxNhiY2Nv+ATV3NzcO86hrqSkBLW1tTh8+DDGjh075H9PBID9+/cjPj4e0dHRGDZsGB599FEcPXrU67AcE4rn7Ga2FsVr167h6tWrAID29nZ8/PHHSEpKciQwL/UdV0dHB44dO4b4+HiPo7JvwoQJmDJlChoaGgAABw4cGPIJGz36nrNr166huroaycnJHkdl35w5c3D69Gk0Njais7MTlZWVWLZsmddhOeLChQsAgK+++grvvvsuCgsLPY7IvqlTp+LIkSNob29HIBDAoUOHQuKa2CMUz9nNbH19ev78eeTl5aGzsxN+vx/Lli1z9WPtQOkZ1/fffw+/349FixZh7ty5XofliC1btmDlypXo7OxEQkKC51/JOKXnnPn9fvj9fuTn52PRokVeh2VbeHg4XnvtNTz00EPw+/1YvXo1UlJSvA7LEfn5+Whra8OwYcOwdetWjBkzxuuQbMvKykJBQQEyMzPh8/lw9913i1/bD0WheM5uZmtRTEhIQH19vfi7y1DVMy7pN8ChLD09HceOHfM6DMf1nLPBVkXHCUuWLMGSJUu8DsNxH3/8sdchuKKsrAxlZWUhORdD9Zz1xS0ZREREBi6KREREBp9Zyrf4l32+iwDOuhfOgJoWCASigZAbF2CMLVTHBYTcOQvVcQGci0NNqI4L6DM2TVCLIhERUSjj16dERESGoLJPx40bF9Du92Xmyy+/NH/hcPmlf/jhB9N2bdPyqFGjgoqrqakJra2tPsDauCRaqaq2tjbT9pkzZ4p9wsLCgo7h+PHjrYFAINrJcWl69j3ebPz48WIfKxVhesYFeH/ORowYIfYJdl+a3bkoxd+zp8wp06dPN23XzqWduWhlXNJ50eaildqk/ZmLfr9f7P/555+btkvHGAj+GmeFW9dF7Vj0VP+52fDhw8U+fUsf9lffc6YJalGMi4sLOp1fKgFmpbSWdmNXrSSQmb63FrIyLol282Sp1JFWVNfK4uHz+c4Czo5LIx17K2XGND3jArw/Z1ppvmC38tidi1L8FRUVQT3PrWzevNm0XTuXduailXHdeeedQT0XYK3kYH/morYlQ1pstm3bJvYJ9hpnhVvXRe1YSMffys3QNX3PmYZfnxIRERm4KBIRERm4KBIRERm4KBIRERls30/xVqQfWLV6qdIPytK9GYG/3cfMjFv3vZOSKbQkAKlY+kDdm88O7XwdOnQo6Oezkmhjl3TOtB/0peSugbrvYA8tUUG6H51WiFoas3SfUAA4ceKEabtb51JKZrJyb8/i4mKxj1v3adXOmXR/R+0aJ5k2bZr4mJU57wbtfopVVVWm7U7e5zIY/KRIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERkcH1LhpQiraXoaun/koHe1iCNS0uPlsYsPRcgbwnQam/aIaWRW0lbH2xbTaStPlZqSmrzt66uzrTdzjmzUitYY2VLiTZP3SDNOa0GclRUlGn7jh07HIgoOMHWwAX07S1W5o+2LcQN0pitzLeBqPVqhp8UiYiIDFwUiYiIDFwUiYiIDFwUiYiIDFwUiYiIDK5nn0oZZNpd2aWMKe0O9W7Qssekgr5alqaUJSgVxAXkrEMt+/FWtGxFKX4rRb+9yD7VzplUSNrpzE43ii1LGa2APC6tj5XMSCnrUyvQ7YaMjAzxMelcalnhbhkzZoyjzyeNe6CL62vXOCnLV4vx7Nmzpu1eZa/zkyIREZGBiyIREZGBiyIREZGBiyIREZGBiyIREZGBiyIREZHB9S0Zzz77bNB9pFTcgS4QayXVXEvht3IstOLHVmnp+NKx145FUVGRabtXBX0lFRUVpu1SEWlA3nqjkY6VlaLqt3pOACgrKwv6+aQxa6nzbsxFK7QYpW1b2lyUtq7Y3VqjxSk9pm2jKS0tNW3Pzs4W+7ixrUHbDiY9po1L2pLmxtam/uAnRSIiIgMXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIoPr2adSpmN5ebnYR8q0e+WVV8Q+VjI7b0V7PYmU4ajRihW7kYGlZUFKj0lF2gE5Q1PLOHOLlmUYCASCfj7p+GvZoOnp6UG/zq1omZ/SOYuPjw/6+dx4Hw0k6T1rpQi+laLp/SXNH+3mAI8//rhpu5YNOpTPp5Vi/E7gJ0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiIDF0UiIiKDI1syrKQua2nrUrryYEo9llK/tQK8UuHmwVJoWaNtyZB4lVIdLG3uSFsy3Nh2YZX2vpDYKU4+UKTrina9kbYBaX28OJfSOSsuLg76uQbTXJScPXs26D7ckkFEROQx24tieXk5Vq1aheLiYrzwwgvo7Ox0Iq5Bwe/3IyMjA0uXLvU6FMesXr0aMTExSE1N9ToURzU0NCA9Pb33v9GjR1sqvjDYhOq4rl+/jrlz5yItLQ0pKSnYsGGD1yE5Ki4uDjNnzkR6ejpmz57tdTiOCNVrx81sLYotLS149dVXsW3bNmzfvh1+vx/V1dVOxea5iooKJCcnex2Go1atWoW9e/d6HYbjkpKSUFdXh7q6Ohw/fhyRkZHIy8vzOizbQnVcw4cPR3V1Nerr61FXV4e9e/fiyJEjXoflqIMHD6Kurg7Hjh3zOhRHhOq142a2Pyl2d3fjhx9+gN/vxw8//IDbb7/dibg819zcjA8++ABr1qzxOhRHLViwAGPHjvU6DFcdOHAA06dPV8vnDUWhNC6fz4eRI0cCALq6utDV1QWfz+dxVKT5R7h2ADYXxcmTJ+P555/Hz372M+Tn5+OnP/0p5syZ41Rsnnr22Wfx8ssv4yc/4c+uQ01lZSUKCwu9DsNxoTYuv9+P9PR0xMTEIDc3F1lZWV6H5Bifz4cHH3wQs2bNwuuvv+51OBQEW9mnly5dQlVVFT7//HNERUVh1apVaGhowM9+9rPevyNlRmnZb1LG30D9lrJ7927ExMRg1qxZQWfWWsnS1IpYDxZWxuVFVlxnZyd27dqFjRs39ruPluUmFWEeaNq4pGztoqIi8fm0LOmBEhYWhrq6Oly+fBl5eXk4efLkDb9XSe93rdC8dO3QMozdyP6uqanBpEmTcOHCBeTm5mLGjBlYsGDBLV9T+xZAylgdCtePtLQ08TFpzF6Ny9bHoP379yM+Ph7jxo3DsGHD8Oijj+Lo0aNOxeaZmpoa7Nq1C3FxcVixYgWqq6vx1FNPeR0W9cOePXuQmZmJ8ePHex2Ko0J1XMDfFuicnJyQ+r1q0qRJAICYmBjk5eWFxHXxH4WtRXHq1Kk4cuQI2tvbEQgEcOjQISQlJTkVm2c2btyI5uZmNDU1obKyEvfffz/eeustr8Oifti5c2dIfcXYI9TGdfHixd5vHzo6OrB//37MmDHD46icce3aNVy9erX3///0pz+FfMZmKLG1KGZlZaGgoAA5OTm499578eOPP6pf2ZD3CgsLcc8996ChoQGxsbH4j//4D69Dckx7ezv27duH5cuXex2Ko0JxXN988w0WLlyIu+++G3PmzEFubm7IbH06f/485s+fj7S0NMydOxePPPIIFi9e7HVYtoXytaMv2xVtysrKsG7dOidiGZRycnKGxHf2/bVz506vQ3BNZGQk2travA7DcaE4rrvvvhsnTpzwOgxXJCQkoL6+3uswHBfK146+mFpJRERk4KJIRERk8AUCgf7/ZZ/vIoDgK7sOTtMCgUA0EHLjAoyxheq4gJA7Z6E6LoBzcagJ1XEBfcamCWpRJCIiCmVBJdqMGzcuIG2OlUgFwk+dOiX2iYiIMG3XXjsyMjKouJqamtDa2uoDrI3L7/ebtn/++ediH2lc2jaWsLCwoOICgOPHj7cGAoFoK+OSaJv3z507Z9oujRcA4uPjg+7TMy7A2jmTtLe3i4/99bh2uXIAABKgSURBVK9/NW3XNr9PmTLFtF06l3bnohS/dF4A4Pvvvw/qNQD5/aeVdrQzF3u2NfS3HfhbVquZ6dOni32sFDJway5K1xVAv2ZKpHFL10u7c1G63jc0NIh9pDFrr233nGmCWhTj4uKCLm4rVQvRqp1IB0O7b1yw1VP6Vq63Mi5pkdBOpPTYwYMHxT5WTr7P5zvb83pOFSOuqqoSHystLTVt146FdC61Pj3j6vl7To1Nq5AiZR5r2weCvdem3bkoxa9VcTl06FBQrwFAvJOFVp3Kzly0cj9F6Z6lmzdvFvs89thjwYQFwL25qP3j00qFqLfffjuo57I7F6XrvZbBL43ZzXOmYaINERGRgYsiERGRgYsiERGRgYsiERGRwXaZt1uxclsWKdnCyo+1bpESRb777juxjxSjdkssN25ro5Fi0eKQEjq0xCjpB3mnsviCoY1NunXUjh07xD5S4olb5QKDTewBgPLyctN2rWSjdIsqLdHGDun1KioqxD5SMtD27dvFPlaSNtyiJUdJyTHarc+kY+jWbd2k99LZs8Fvd9TqaEtjduKWaPykSEREZOCiSEREZOCiSEREZOCiSEREZOCiSEREZOCiSEREZHBkS4ZWO1JKXddSpKUUb7dSvyVaqr5Uf1GqAwrI6dZS2j8gj9mtrQtSSrN2jqWtJlI6OOBeSrgV2nYeaVuJNjYtRd4N2tYXiRSjtj3IiXT3YCxcuNC0XTtf0ntWm2+DaXuQFqd0/Rjo95KV6722vSLY59JicGLbEz8pEhERGbgoEhERGbgoEhERGbgoEhERGbgoEhERGRzJPrVSjNtKhp5WLFfKOrNTUFvLtpMyvrTXk55PG5eU5epWJq70vNo5lrJnB1Mmo0aLU8u0k7iRtVhVVSU+JmVya1mJ0vnUCjdr89QNUqFuqeg3IL9fBjoj2CrtGEvzVBubG+fMSnFvKxnS0rkE3D2f/KRIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERkcGRLhpY6O23aNNN2rQi2xMrWDzvi4+PFx6SUYCtbDbTUeSupzHZIx1jbAiIV4XWiOO9A0LZdSCnt2jYON8Z98OBB8TFpu4a2jcMKaS5qx8IN2vGViohr2zjcKvytXRelx7Q+0jzVitMPlq1P2nXMyk0P3FwL+EmRiIjIwEWRiIjIwEWRiIjIwEWRiIjIwEWRiIjI4Ej2qZZJKmWmWcn40jKp3MiykgoSA0BRUZFpu1aAVxqzlj1mpSD1rWhFy8vKykzb09LSxD5a/ANNy96T5ul3330n9iktLTVtd6sgu0Q7Z9K4tPNSUVFh2i4VFwcGz5i1TEYp2z0jI8OBiIKjFa2W3mca6dwMdJZ3dna2+FhUVJRpu5ahLF0XtQxTN7Nq+UmRiIjIwEWRiIjIwEWRiIjIwEWRiIjIwEWRiIjIwEWRiIjI4MiWDK2gtZQ6q6V3SynmWlq6lGLuFil+7VhIqcf19fViHy1F3iotPV1KaddilM6XlTRsu7T0dCvH30pBditz41a0FHRpzNrxl87zQG+70EjbFrStJtIWGmmrgJusFNHX+khzUXsvSY/Zef9ZmYtacXqpiLt2ztycp/ykSEREZLC9KO7duxdJSUlITEzEpk2bnIhpUAjFcZ07dw4LFy7Er371K/zTP/0T3n//fa9DckzP2JKTk5GSkjLg3xy4paGhAenp6b3/jR49esBv1eSW8vJypKSkIDU1FYWFhbh+/brXITkiVOciEJrXxZvZ+vrU7/dj7dq12LdvH2JjYzFnzhwsW7YMd911l1PxeSJUxxUeHo7Nmzfj3Llz6OjowL/8y78gPT0dU6ZM8To023rGlpmZiatXr2LWrFnIzc0d8ucsKSmpt6qR3+/H5MmTkZeX53FU9rW0tODVV1/FqVOnMGLECDz55JOorKwcVF/fWhWqczFUr4s3s/VJ8ejRo0hMTERCQgIiIiKwYsUKx29s6oVQHdfEiRORmZkJABgxYgRiY2PR1tbmcVTO6Du2UaNGITk5GS0tLR5H5awDBw5g+vTp4u+BQ013dzc6OjrQ3d2N9vZ2TJo0yeuQHBGqczFUr4s3s7UotrS03PApIzY2NiROfqiOq6/z58/jzJkzuPPOO70OxXFNTU04ceIEsrKyvA7FUZWVlSgsLPQ6DEdMnjwZzz//PKZOnYqJEyciKioKDz74oNdhOS6U5uI/wnURsPn1aSAQ+Ls2n893w5+ljCktk1Qqqq39lqIV7w5Wf8YlxaIVpJYK3G7YsEHs48bXSQ888ACys7Oxbds2LF++/IbHpOOoZWFKj2mF4qU+djI0AeD7779Hfn4+XnnlFYwePfqGx6Ti6to5kzIdtQxIKbPPztg6Ozuxa9cubNy48e8ek+LX/hXvdRH3S5cuoaqqCo2NjbjtttvwxBNP4K233sJTTz3V+3ekzGttXknFqu3OKyu0uWjl5gBSZqeUvak9n5XsUzvXRY1UON2r385tfVKMjY3FuXPnev/c3NwcEl+BhOq4AKCrqwv5+flYuXLl3y2IQ10oj23Pnj3IzMzE+PHjvQ7FEfv370d8fDyio6MxbNgwLF++HJ9++qnXYTkmFOdiKF8X+7K1KM6ZMwenT59GY2MjOjs7UVlZiWXLljkVm2dCdVyBQAAlJSVITk7Gc88953U4jgrlsQHAzp07Q+arUwCYOnUqjhw5gvb2dgQCARw4cADJycleh+WIUJ2LoXpdvJmtRTE8PByvvfYaHnroISQnJ+PJJ59ESkqKU7F5JlTHVVNTgzfffBPV1dW9Kf4ffvih12E5IpTH1t7ejn379oXMJw4AyMrKQkFBATIzMzFz5kz8+OOPePrpp70OyxGhOhdD9bp4M9sVbZYsWYIlS5Y4EcugEorjmj9/vunvAqEglMcWGRkZMlnCfZWVlVm62e5gF8pzMRSvizdjRRsiIiIDF0UiIiKDL5iP+T6f7yKAs+6FM6CmBQKBaCDkxgUYYwvVcQEhd85CdVwA5+JQE6rjAvqMTRPUokhERBTK+PUpERGRIajs03HjxgXcug9eXw0NDabtfr9f7JOUlGTaHhYWZtre1NSE1tZWH+DsuLQYv/76a9P2H374QeyTmJgYdAzHjx9vDQQC0U6OS6o6Afxty4AZ6ZwA8nnR9IwLkM+Zdvz7bjzuS6o0BAAjR440bY+Pjxf7BDs2u3NROjfauKQYtdceNWpUMGEBsDcXpYzb8+fPi306OjpM27XXvv3224OKC+jfXNR8/vnnpu2dnZ1in4iICNN2bQN9sGPrz1yU3u8A8MUXXwT1eoA8rpiYGLHPuHHjTNu1917fc6YJalGMi4vDsWPHguliiVTOSHuTHzx40LRduiHm7Nmze//fyXFpMUql7bQFx0o5Lp/PdxZwdlxauTmpfJp0TgD9RqWSnnEB8ti04y+VD7RSWksrexfs2OzORencaOOSYty2bZvYR7uBs8TOXJSOsVb+S7phtNOlFPszFzXSInr2rPwT3sSJE03bnRxbf+ai9H4H9BuYS6RxSe9XQB6X9t7re840/PqUiIjIwEWRiIjIwEWRiIjIYLvMm1XaraMOHTpk2h4VFSX2kX5LsvLblR3a7y7S7x0DTfvdTfqu3kqfgT72gP77rPQ7jvbbhfT7iXb7Iu1WVG6Qjr82F6Xf5bTbEDU2Npq220nm0n6fKi4uNm3XbrIsXSOk5wLkc+nm/JXmnHY8duzYYdqujU26ZZadW2lp57u0tDTo55N+O163bp3YR4rfyu/eN+MnRSIiIgMXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIoPrWzKkdHEpvVijpREPRE3W/tDSuMvLy03btbJVbtC2V1RVVZm2Z2dni320LQ0DTZsj0mPSmAE5XVw7hgO9PUhKQ9fS+6XtQVpKvRvvMe18SWXqHnvsMbGPtNWrrKxM7OPFdi7pPaPNRSvXTDfOmXZcpGuZdo377rvvTNu1a46dLSW3wk+KREREBi6KREREBi6KREREBi6KREREBi6KREREBkeyT7UCyFYypiRaxt9goR0LKwWp3aAVzZZ4Udx7oGzfvl18TJpzWmbnYDlWVjIP3czqC5aWZeqkwXRdSUtLC7qPdpPhwTIXrVxznLyRdzD4SZGIiMjARZGIiMjARZGIiMjARZGIiMjARZGIiMjARZGIiMjgekFwqQi2lvq9cOFC0/bBVHhaKtwrjRcYPFsyrNC2mkhFmKVC1bd6bKBpx18b92Cnpa0XFRWZtmtp8FJxfzu0rS3SHJEKSFsljXmgC/UD+jYaqUC2VDgdkOf2QG/V0OaOdPytjMsJ/KRIRERk4KJIRERk4KJIRERk4KJIRERk4KJIRERkcCT71EqWoZUivFaKytqhZZ+tW7cu6OfTCk8PdlrGn5QlVlZWJvaRjoUbGY63os1fKUtayrgF9AzOwUKa22PGjBH7SJm4djKJz549Kz4mZWJq1w7p+bTi4l7MOSukOSdl6wPyXBzojHdtt4F0/LX3GLNPiYiIBgAXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIgMXRSIiIoPrBcGHMi2NuLS01LRdKyBdXFxs2m6l8K2dNHitr1TQXNuCIqVUa1sTpHRrN9PjpeLTWoq/tC1gx44dYh9pu4OdIsxajFZS9S9duhR0DNLxszMXta0S0mPa60nHSZuLA10cG5BvKHDw4EGxj3adGEjaXLSyVUJ7L0mkuahds/uLnxSJiIgMthbF1atXIyYmBqmpqU7FMyicO3cOCxcuRFFREVatWoV33nnH65Acc/nyZRQUFGDGjBlITk7GZ5995nVIjrh+/Trmzp2LtLQ0pKSkYMOGDV6H5Iiecc2fPx/33HMPNm7c6HVIjmhoaEB6enrvf6NHj/bkVk1u4Fwc2mx9fbpq1Sr86le/wi9/+Uun4hkUwsPDsXnzZly5cgXt7e145plnMHv2bPVeZ0NFaWkpFi9ejHfeeQednZ1ob2/3OiRHDB8+HNXV1Rg5ciS6urowf/58PPzww5g3b57XodnSM67u7m50dXXh4YcfxqJFizBnzhyvQ7MlKSmp9yswv9+PyZMnIy8vz+OonMG5OLTZ+qS4YMECjB071qlYBo2JEyciMzMTABAZGYmpU6eitbXV46jsu3LlCg4fPoySkhIAQEREhCe/p7jB5/Nh5MiRAICuri50dXXB5/N5HJV9oTquvg4cOIDp06dj2rRpXofiiFA9Z6E6rpvxN8Vb+Pbbb/Hll18iOTnZ61BsO3PmDKKjo1FcXIyMjAysWbMG165d8zosx/j9fqSnpyMmJga5ubnIysryOiRH+P1+3HfffbjzzjuRk5OD2bNnex2SoyorK1FYWOh1GI7iXBy6PMs+1T6hZGdnm7ZrmZ1umD17NrKzs/Hv//7veOSRR254zErGnZSZpY3LyU9y3d3dqK2txZYtW5CVlYXS0lJs2rQJL7zwwi1j1GiFeyVWMs5uJSwsDHV1dbh8+TLy8vJw8uTJG37vljJb6+vrxeeMiooybS8qKhL7OP3pOywsDJ9//nnvuJqbm28Yl5SVKGXoaY9p2aCPP/54PyPuv87OTuzatcv09ynpfXHo0CHx+aTs6YH+RuRWc1H6nVGbixJtLjqdzR0WFob3338fV65cwTPPPIM///nPSEpK6n1cmlfauKTrvZbx7kSWqYSfFAVdXV3Iz8/HypUrsXz5cq/DcURsbCxiY2N7/9VaUFCA2tpaj6Ny3m233YacnBzs3bvX61AcFYrj2rNnDzIzMzF+/HivQ3FFKJ4zABg9ejTmzZun/gNlqOKiaCIQCKCkpATJycl47rnnvA7HMRMmTMCUKVPQ0NAA4G+/5dx1110eR+WMixcv9u6f6ujowP79+zFjxgyPo7IvVMfVY+fOnSH31WmonrO+47p+/To++eQTTJ8+3eOonGfr69PCwkJ89NFHaG1tRWxsLMrKynqTOIaympoavPnmm5g5c2bvx/QXX3wRS5Ys8Tgy+7Zs2YKVK1eis7MTCQkJQ/oej3198803KCoqgt/vx48//ognn3wSS5cu9Tos20J1XADQ3t6Offv2Ydu2bV6H4qhQPWc94+ro6EAgEMAjjzyCBx54wOuwHGdrUdy5c6dTcQwq8+fPRyAQ8DoMV6Snp+PYsWNeh+G4u+++GydOnPA6DMeF6riAv2V2t7W1eR2G40L1nPWMa6Bv9j7Q+PUpERGRgYsiERGRwRfM14Q+n+8igLPuhTOgpgUCgWgg5MYFGGML1XEBIXfOQnVcAOfiUBOq4wL6jE0T1KJIREQUyvj1KRERkYGLIhERkYGLIhERkYGLIhERkYGLIhERkYGLIhERkYGLIhERkYGLIhERkYGLIhERkeH/A8Gqa5vLR9/NAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 64 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the figure\n",
    "fig = plt.figure(figsize=(6, 6))  # figure size in inches\n",
    "fig.subplots_adjust(left=0, right=1, bottom=0, top=1, hspace=0.05, wspace=0.05)\n",
    "\n",
    "# plot the digits: each image is 8x8 pixels\n",
    "for i in range(64):\n",
    "    ax = fig.add_subplot(8, 8, i + 1, xticks=[], yticks=[])\n",
    "    ax.imshow(digits.images[i], cmap=plt.cm.binary, interpolation='nearest')\n",
    "    \n",
    "    # label the image with the target value\n",
    "    ax.text(0, 7, str(digits.target[i]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can quickly classify the digits using a random forest as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn.cross_validation import train_test_split\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "Xtrain, Xtest, ytrain, ytest = train_test_split(digits.data, digits.target,\n",
    "                                                random_state=0)\n",
    "model = RandomForestClassifier(n_estimators=1000)\n",
    "model.fit(Xtrain, ytrain)\n",
    "ypred = model.predict(Xtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can take a look at the classification report for this classifier:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.97      0.99        38\n",
      "           1       1.00      0.96      0.98        45\n",
      "           2       0.95      1.00      0.98        42\n",
      "           3       0.98      0.98      0.98        45\n",
      "           4       0.97      1.00      0.99        37\n",
      "           5       0.98      0.98      0.98        48\n",
      "           6       1.00      1.00      1.00        52\n",
      "           7       1.00      0.96      0.98        50\n",
      "           8       0.94      0.98      0.96        46\n",
      "           9       0.98      0.98      0.98        47\n",
      "\n",
      "   micro avg       0.98      0.98      0.98       450\n",
      "   macro avg       0.98      0.98      0.98       450\n",
      "weighted avg       0.98      0.98      0.98       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "print(metrics.classification_report(ypred, ytest))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And for good measure, plot the confusion matrix:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "mat = confusion_matrix(ytest, ypred)\n",
    "sns.heatmap(mat.T, square=True, annot=True, fmt='d', cbar=False)\n",
    "plt.xlabel('true label')\n",
    "plt.ylabel('predicted label');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We find that a simple, untuned random forest results in a very accurate classification of the digits data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary of Random Forests\n",
    "\n",
    "This section contained a brief introduction to the concept of *ensemble estimators*, and in particular the random forest – an ensemble of randomized decision trees.\n",
    "\n",
    "**Question:** What advantages does the random forests method have?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.reduce overfitting 2. working with a subset of data => faster training speed and greater compliance with high dimentionality data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** What disadvantages does random forests method have?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. interpretability: RF are like black boxes 2. the number of trees can be a problem, as the larger the number gets, the larger memory space will be required"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Boosting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** How does boosting work?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question:** What can we see after each time we run the boosting algorithm?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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nSjqGZOLHuo5tvg68GEDSD5KE8p4iG2rVMzsL69fDmjXJ5exs2S0yazRnsR3BOWw2Gj3HIEfEQUlvATYCE8CHImKbpNXAdESsA94O/LmkXyM55PeGiOg89GcNMjsLq1bBpk3JZNdFi2DlSti4MTntqpkVy1lsnZzDZqOTZ5IeEXELcEvHbe/KfH838IJim2ZVtn49fOYzh5ZGnJlJQnrDBjj//HLbZtZUzmLL2rAhyd2ZmeT6zAzccYdz2KwIPpOe9W12Ft72tiPXDd+/H7ZuLadNZmZtc+edh4rjOfv3w+c/X057zJrEBbL1bcMG2N1lddUnPhGWLx9/e8zM2mi+8cYHD463HWZN5ALZ+rZlS/ezTp54IkxNjb89ZmZtNN8446NyDZ40s4W4QLa+rVgBixcfftuxx8If/qEnhpiZjcuP/VgyMS9r0SI444xy2mPWJC6QrW9TU8lM6cWLQUouX/ACTwoxMxunqSk466zDs/iss3wkz6wIPhBjfZuYSJYR2rAhmZS3fHkSyO49NjMbH2ex2ei4QLaBTEwkPcbuNTYzK4+z2Gw0PMTCzMzMzCzDBbKZmZmZWYYLZDMbnb174eyz4Z57ym6JmVl7OYv75gLZzEbn+uvh9tvhssvKbomZWXs5i/vmAtnMRiMCrr4aHnssCeYNG8pukZlZ+ziLB+IC2cxG47bbYN++5PsDB+CSS7qfgnHcfKjRzNqkillcgxx2gWxmo3HNNbB//6Hr+/bBVVeV1545PtRoZm1SxSyuQQ67QDaz0di+PTm0N+fAAbj55vLaAz7UaGbtU7UsrkkO+0QhNTY7m7yvtmyBFSt8BiWrmG3bym7Bkbodaty5E449ttx2WW05h63yqpbFNclhF8g1NTsLq1bBpk3JkZNFi2DlyuS0ow5ns3nMd6jxyitLa5LVl3PYbAA1yWEPsaipDRuSUJ6ZSY5WzMwk1yt6pMIsn1FP3JjvUGMNJoxY9TiHrbFGmYk1yWEXyDW1Zcvh/4BBcn3r1nLaY1aIUU/c2LYtCebs1+bNtZgwYtXjHLbGGmUm1iSHXSDX1IoVyeG8rEWLYPnyctpjNrSyJm7UZMKIVY9z2BqpjEysYA67QK6pqalkrNvixSAllytXJreb1VJZa3VWcY1QqwXnsDVSGZlYwRx2gVxTExPJRJC1a2H16uTSE0Os1spaq7OKa4RaLTiHrZHKyMQK5nCuAlnSuZK2S9oh6fJ5tnm1pLslbZP0d8U207qZmIDzz4crrkguHcpWa2Wt1Vm1NULn4RyuJuewNU4ZmVjBHO65zJukCeBa4CXALmCzpHURcXdmm9OA3wReEBEPSnr6qBpsZg1V1lqdVVsjtAvnsJmNTRmZWMEcztODfCawIyJ2RsQjwA3ABR3bvAm4NiIeBIiI+4ttpplZqzmHzczGKE+BfBJwb+b6rvS2rOcCz5X0GUl3SDq3qAaa2QAqtp6kDc05bFZHzuLaylMgq8tt0XH9KOA04IXARcBfSHrKEQ8kXSppWtL0nj17+m1r5c3Owvr1sGZNcjk7W3aLrLUqtp6kDa2wHAZnsdnYOItrK8+ppncBSzPXTwZ2d9nmjoh4FPiqpO0kQb05u1FEXAdcBzA5OdkZ7rXmU45aZXRbT9LrTtVdYTkMzmKzsXAW11qeHuTNwGmSTpV0DHAhsK5jm38AXgQgaQnJob6dRTa06nzKUauMCq4naUNzDufkLLbKcBbXWs8COSIOAm8BNgJfBm6KiG2SVkt6RbrZRmCvpLuBTwG/ERF7i2xo1Q+Z+ZSjVhllryfpMXeFq0oOg7PYLLcys9g5PLQ8QyyIiFuAWzpue1fm+wDeln4Vrg6HzOZOOTozc+g2n3LUSjHfepJXXjme58+Oudu4cTzP2QJl5zA4i836UmYWO4eHVosz6fVzyKys3g2fctQqY9u25A8l+7X5iGGoo9FtzJ01Rt4sLrOX2VlslVFWFjuHC5GrB7lsCx0yO//8Q7eV2bsxd8rRDRuSdi1fngRyVXpVzMai25i7nTvh2GPLbZcVIk8Wl93L7Cy21nMOF6IWBXLeQ2bZ3g041Luxfn0Sjlu2JI81qrCcO+Votmgfp9nZ5DUY9X6azWu+MXfjGt5hI5Uni8vOYXAWW8s5hwtRiwJ57pBZZ49E5yGzbr0bMzPwtrfB/fdXd8xcEcrutTEDyh//bCOVJ4vbnMPgLLYKcA4XohYFct5DZt16N449FnbvPrSySnbMXFm9C6OwYQPcccehD6aZmeR60/bTKm7btrJbYCOUJ4vbnMPgLLYKcA4XohaT9ODQIbMrrkguu/0n3m1yxoknwsMPH75dE5f8ufPO7mMDP//5ctpjZs3UK4vbnMPgLDZrilr0IOfVrXdjdhYuvrj5S/7MN0v84MHxtsPM2q3NOQzOYrOmaFSBDEdOzpidzTd+ue7mG9t2VON+wzWydy+88pXJhIm3vhU+/GFYtqzsVpmNXFtzGJzFlbR3L7z85ckb8cYbncOWS22GWAxqrjdj7VpYvTq5bOJkiR/7seRQZtaiRXDGGeW0xzi0UPuFFx5asD0PnwEpP79WtdCWHAZncSVdf30yEPxzn8ufw+B8yauhr1PjC2TIN3657rqN+zvrrGb20NRCdqH2//iP/hZsz54ByRbm16o22pDD4CyunLksnlvV4dOfzn/iDOdLPg19nRTZpUDGaHJyMqanp0t57qaaW3vTi+NXwK23wstedvigS4BnPnPhBdsjYOlS+MY34ElPgo99zJ+s86n4ayXpzoiYLLsdvTiLi+csrpBbb4Vzz4X/+q9Dtz3jGfDVry584oyK50tl1OB1GjSLW9GD3BZt6aGphc6F2ufMLdg+n25nQJpbG8sO59fKKspZXCHXXHN4cQzwwAML5zA4X/Jq8OvkAtlsFDoXap8zt2D7fOY7A5Idya+VmfWyffuRtx08uHAOg/Mlrwa/Ti6QzUZh27akQO72tXnz/D833xmQ7Eh+rcysl/myeKEcBudLXg1+nbzwjFmV+AxI+fm1MrNRcb7k0+DXyT3IZmZmZmYZrelBnptVvGULrFjhWcVmZuPmHDazumhFgTw7C6tWHXkWp6YuVG9mVjXOYTOrk1YMsdiwIQnlmZlkLPnMTHI971rh4zA7C+vXw5o1yeXsbNktMjMrTh1yGJzFZpZoRQ/yli1HLkm7f3+yiPv555fTpiz3rJhZ01U9h8FZbGaHtKIHecWKJOiyFi1KznBUBXXpWTEzG1TVcxicxWZ2SCsK5KmppBdg8WKQksuVK6tzNsSFelbMzJqg6jkMzmIzOyRXgSzpXEnbJe2QdPkC271KUkjq+5zXozQxkRwiW7sWVq9OLqt0yKwOPStmVr46Z3HVcxicxWZ2SM8xyJImgGuBlwC7gM2S1kXE3R3bHQf8CrBpFA0d1sREMs6tKmPdsuZ6VjrHvVWpZ8XMytWELK5yDoOz2MwOyTNJ70xgR0TsBJB0A3ABcHfHdmuA9wK/XmgLW2CuZ2XDhuRQ3vLlg60P6jVGzRrNWTxiRWSxc9isGfIUyCcB92au7wJWZjeQtAJYGhHrJTmUBzBsz4pnX5s1nrN4DIbJYuewWXPkGYOsLrfF43dKTwCuBt7e84GkSyVNS5res2dP/lZaT22bfe21Sq2FnMUV17YcBmexNVeeHuRdwNLM9ZOB3ZnrxwHPA/5NEsAzgHWSXhER09kHiojrgOsAJicnAytMHdYYLYp7aaylnMUV16YcBmexNVueHuTNwGmSTpV0DHAhsG7uzojYFxFLImJZRCwD7gCOCGQbrTbNvm5jL40ZzuLKa1MOg7PYmq1ngRwRB4G3ABuBLwM3RcQ2SaslvWLUDbR86rDGaFG8Vqm1kbO4+tqUw+AstmbLdarpiLgFuKXjtnfNs+0Lh2+W9auolTDqYK6XZmbm0G1N7qXpxbPm28NZXG1tymFwFndyFjdLrgLZ6qHqa4wWxWuVHuIxgGbV0pYcBmdxlrO4eVwgW+20rZdmIdkxgHD4GMA2fECbWXmcxYc4i5vHBbLVUpt6aRbStlnzZlYtzuKEs7h58qxiYWYV1bZZ82ZmVeQsbh4XyGY11rZZ82ZmVeQsbh4PsTCrMY8BNDMrn7O4eVwgm9WcxwCamZXPWdwsHmJhZmZmZpbhAtnMzMzMLMNDLCrKZ+QxMyuXc9isvVwgV5DPyGNmVi7nsFm7eYhFBWXPyBNx+Bl5zMxs9JzDZu3mArmCFjojj5mZjZ5z2KzdXCBXkM/IY2ZWLuewWbu5QK4gn5HHzKxczmGzdvMkvQryGXnMzMrlHDZrNxfIFeUz8piZlcs5bNZeHmJhZmZmZpbhHuQa8aL1ZmblcxabNZ8L5JrwovVmZuVzFpu1g4dY1IQXrTczK5+z2KwdXCDXhBetNzMrn7PYrB1cINeEF603Myufs9isHXIVyJLOlbRd0g5Jl3e5/22S7pZ0l6RPSnpW8U1tt/kWrX/pS2H9elizJrmcnS27pWY2Cs7hanAWm7VDz0l6kiaAa4GXALuAzZLWRcTdmc22AJMRcUDSLwLvBV4ziga3VbdF61/6UjjvPE8WMWs653B1OIvN2iHPKhZnAjsiYieApBuAC4DHgzkiPpXZ/g7g4iIbOS5VX7qnc9H69esPTRaBwyeLeGF7s0ZpTQ6Ds9jMypenQD4JuDdzfRewcoHtLwG6zueVdClwKcApp5ySs4njUcelexaaLOJQNmuUwnIYnMVFcxabNU+eMcjqclt03VC6GJgE/qDb/RFxXURMRsTkCSeckL+VY1DHpXvKnCwyO+vxdmZjVFgOg7O4aGVlsXPYbHTy9CDvApZmrp8M7O7cSNI5wG8DZ0fEw8U0b3zq2AMwN1mks6dlamq0z1vHHh6zmmtFDoOzOC/nsNlo5SmQNwOnSToV+AZwIfDa7AaSVgAfBM6NiPsLb+UYzPUAzI0hg/56AMoYM9dtskjRz9ttv7I9PODxdmZj0IocBmdxN85hs/HrWSBHxEFJbwE2AhPAhyJim6TVwHRErCM5lLcY+KgkgK9HxCtG2O7CDdMDUOZ/8p2TRYo033791E/Vr4fHbD5VnxAG7clhcBZ3cg5bG1Qxh/P0IBMRtwC3dNz2rsz35xTcrrEbpgegqf/Jz7dfz39+vh6eKr7hzbLqdJi6DTkMzuJOw+YwOIut2qqaw7kK5LYYtAegjmPm8phvv446qncPT1Xf8GZZTSyomsBZfMgwOQzOYqu+quawTzVdgKaeenS+/TrjjCRc166F1auTy86wreNM9Lprw4z2ovdxoYLK6qeJWTxMDoOzeNzakMNQ7H5WNYfdg1yAslaTGLWF9qtXD08Te3KqrA29RKPYx2EnhFm1NDGLh8lhcBaPUxtyGIrfz6rmsAvkAoxjNYkyDLNfVX3DN1VVD1EVaRT72MSCqs2amMXD7pOzeHzakMNQ/H5WNYddIBdklKtJlGnQ/arqG76p2tBLNIp9bGJB1XZNzOJh9slZPD5tyGEofj+rmsMukG0kqvqGb6o29BKNah+bWFCZzXEWj08bchhGs59VzGFFdD1b6chNTk7G9PR0Kc9t1jRVG/s2imWlqraPvUi6MyImy25HL85is2JUMaOcxYNnsXuQzRqgSr1EowrPKu2jmVmnqmWUs3g47kE2s6FleykefRSuvvrww2+LFyfLUFXp8NmouQfZzMbNWXwk9yCbWSk6eymOPhoeeeTwbZo4UcXMrEqcxcVygbwAn57T+tHW90vnkj+dgQzNnKhi49PWvy3rX5vfK87iYrlAnkfdBqFbuar4fhnXB0W3JX8AjjkmOcTnZaVsGFX827Jqqup7xVlcTy6Q59GWBb+tGFV7v4zzg2K+JX/e9rYkmJs6gcPGo2p/W1ZdVXyvOIvr6wllN6CqqnpucKumqr1fsh8UEYd/UBRt7kQEixeDlFyedRa8+91wxRXJB5MD2QZVtb8tq64qvlecxfXlHuR5tGXBbytG1d4v4zyjU1OX/GnzWMYqqdrfllVXFd8rzuLhlJnDLpDn4dNzWj+q9n4Z9wdFFc+CNIyqjmVso6r9bVl1VfG94iweXNk57AJ5Hk38T8xGp2rvlyp+UNRJFccytlXV/rasuqr4XnEWD67sHHaBvIAm/Sdmo1cjBACrAAAgAElEQVSl90sVPyjqZJyHRa23Kv1tWbVV7b3iLB5c2TnsAtmsoaryQVHHsbxVHMtoZvXkLB5M2TnsAtnMRmbUY8hGFfg+LGpmTTLKLG5qDrtANrORGeUYsl6BP0xo+7ComTXJqLI4T+E9aBaXncMukM1sZEY5hmyhwJ+aGr63pCqHRc3MhjWqLO5VeA/bc11mDuc6UYikcyVtl7RD0uVd7n+ipBvT+zdJWlZ0Q82sfubGkGUVNYZsocAf5+L84+QsNrNBjCqLe52cpc5Z3LNAljQBXAtMAacDF0k6vWOzS4AHI+I5wNXA7xfdUDOrn25ndipqDNlCgV/FM2oNy1lsZoMaVRb3KrzrnMV5hlicCeyIiJ0Akm4ALgDuzmxzAXBl+v3HgD+WpIiIAttqZjUzyjFkvSZwNHAVCmexmQ1kVFncK4fLXoliGHkK5JOAezPXdwEr59smIg5K2gc8DXggu5GkS4FLAU455ZQBm2xmdTKqMWQLBX7Zs59HxFlsZgMbRRb3KrzrnMV5CmR1ua2zNyLPNkTEdcB1AJOTk+7RMLOhzBf4Zc9+HhFnsZlVzkKFd52zOE+BvAtYmrl+MrB7nm12SToKOB74ViEtNDMbQANXoXAWm1nt1DWL86xisRk4TdKpko4BLgTWdWyzDvj59PtXAf/qMW9mZoVyFpuZjUnPHuR0HNtbgI3ABPChiNgmaTUwHRHrgL8EPiJpB0lvxYWjbLSZWds4i83MxkdldS5I2gN8LefmS+iYZNICbdtn72/ztW2fvz8ijiu7Eb04ixfUtv2F9u2z97f5Bsri0s6kFxEn5N1W0nRETI6yPVXTtn32/jZf2/ZZ0nTZbcjDWTy/tu0vtG+fvb/NN2gW5zqTnpmZmZlZW7hANjMzMzPLqEuBfF3ZDShB2/bZ+9t8bdvnJu5vE/dpIW3bX2jfPnt/m2+gfS5tkp6ZmZmZWRXVpQfZzMzMzGwsXCCbmZmZmWVUqkCWdK6k7ZJ2SLq8y/1PlHRjev8mScvG38ri5Njft0m6W9Jdkj4p6VlltLNIvfY5s92rJIWkWi9Hk2d/Jb06/T1vk/R3425jkXK8p0+R9ClJW9L39XlltLMokj4k6X5JX5rnfkn6QPp63CXpjHG3cRDO4iPub1QWty2HwVnc5X5ncS8RUYkvkjNDfQX4PuAY4AvA6R3b/BLwZ+n3FwI3lt3uEe/vi4Anpd//Yp33N+8+p9sdB9wK3AFMlt3uEf+OTwO2AE9Nrz+97HaPeH+vA34x/f504J6y2z3kPv834AzgS/Pcfx6wARBwFrCp7DYX9Ht0Fleg7aPa33S7RuRwH79jZ3EF2j7EPheexVXqQT4T2BEROyPiEeAG4IKObS4APpx+/zHgxZI0xjYWqef+RsSnIuJAevUO4OQxt7FoeX7HAGuA9wIPjbNxI5Bnf98EXBsRDwJExP1jbmOR8uxvAE9Ovz8e2D3G9hUuIm4lOaXzfC4A/joSdwBPkfTM8bRuYM7iZmdx23IYnMXO4gGyuEoF8knAvZnru9Lbum4TEQeBfcDTxtK64uXZ36xLSP77qbOe+yxpBbA0ItaPs2Ejkud3/FzguZI+I+kOSeeOrXXFy7O/VwIXS9oF3AL88niaVpp+/86rwFnc7CxuWw6Ds9hZPEAWl3aq6S669T50rkGXZ5u6yL0vki4GJoGzR9qi0VtwnyU9AbgaeMO4GjRieX7HR5Ec2nshSa/UbZKeFxHfHnHbRiHP/l4EXB8R75f0E8BH0v19bPTNK0UdM8tZ3OwsblsOg7MYnMV9Z1aVepB3AUsz10/myC7/x7eRdBTJYYGFutSrLM/+Iukc4LeBV0TEw2Nq26j02ufjgOcB/ybpHpJxQutqPEEk73v6HyPi0Yj4KrCdJKTrKM/+XgLcBBARnwWOBZaMpXXlyPV3XjHO4mZncdtyGJzFzuIBsrhKBfJm4DRJp0o6hmTix7qObdYBP59+/yrgXyMdfV1DPfc3Pcz1QZJArvN4qDkL7nNE7IuIJRGxLCKWkYz1e0VETJfT3KHleU//A8kEICQtITnMt3OsrSxOnv39OvBiAEk/SBLKe8bayvFaB7w+nUF9FrAvIu4ru1E9OIubncVty2FwFjuLB8nismcedpll+L9JZl/+dnrbapI/Tkh+gR8FdgCfA76v7DaPeH//BfgmsDX9Wld2m0e9zx3b/hv1nz3d63cs4A+Bu4EvAheW3eYR7+/pwGdIZlVvBV5adpuH3N+1wH3AoyQ9FJcAbwbenPn9Xpu+Hl+sy/vZWdzsLG5bDuf8HTuLK9DuIfa38Cz2qabNzMzMzDKqNMTCzMzMzKx0LpDNzMzMzDJcIJuZmZmZZbhANjMzMzPLcIFsZmZmZpbhAtnMzMzMLMMFspmZmZlZhgtkMzMzM7MMF8hmZmZmZhkukM3MzMzMMlwgm5mZmZlluEA2MzMzM8twgWxmZmatJWmZpJB0VNltsepwgWxjJ2km8/WYpP/KXH/dEI97h6SLF7j/B9IQnHuu/5S0TtKL+niON0v6l0HbaGY2H0lvkPRFSQfSfPpTSU/p4+fvkXROge0p9PF6PNeVkv6moMcKSc8p4rG6PPYLJe0axWNbtbhAtrGLiMVzX8DXgZdnbvvbET/9bOa5VwC3AuslXTji5zUzm5ektwO/D/wGcDxwFvAs4J8lHVNm28zayAWyVY6kCUnvlLRT0gOS/nauF0XSIkk3SPqWpG9L2iTpqZLeD/w48Bdp7/D7ez1PRNwXEe8Dfg/4g8zzv0vSVyV9V9KXJL0svX0FcA3wwrke6PT2n5H0BUnfkfQ1Sb9V/KtiZk0l6cnAe4Bfjoh/iohHI+Ie4NUkRfLF6XbXS/qdzM893psp6SPAKcDH03x6R2bowKWSdku6Ly3EGeTx5mn7myTtSDN5naQTM/dFetTtPyQ9KOlaSeryGOcCvwW8Jn2uL6S3Hy/pL9N2f0PS70iaSO97jqRPS9qXfk7cmN5+a/qwX0gf6zVdnm9C0vvSn9sJvKzj/jdK+nL6GbBT0mXp7YuADcCJmSORJ0o6U9Jn08+k+yT9sf+pqT8XyFZFvwG8FPhJ4GTgUeDq9L5fAI4CTgKWAG8BHomItwObgV9Ie4jffsSjzu9/AidLOjW9vh14Pkkvzu8DN0haEhFbgLcC/5Y+xzPS7b8DvBZ4CvAzwK+ngW9mlsfzgWNJsuhxETFDUpC9pNcDRMTPcfgRufdm7n4RcBpJrl6eZ9hEj8cDQNJPk3QwvBp4JvA14IaOzc4n6bz40XS7VV2e65+A3wVuTJ/rR9O7PgwcBJ5DcsTvpSSfAQBrgE8ATyX5nPij9LH+W3r/j6aPdWOX3XtT2q4VwCTwqo7770/vfzLwRuBqSWdExH5gCtidOeq5G5gFfo3kM+kngBcDv9Tlea1GXCBbFV0GXB4RuyPiIZKeldekPQ+PAicAz46IgxGxOQ2tYexOL78HICJuTHuXH4uIjwDfAH5svh+OiE9GxLZ0+88DNwFnD9kmM2uPJcADEXGwy333pfcP4z0RsT8ivgj8FXDRkI8353XAhyLi8xHxMPCbwE9IWpbZ5qqI+HZEfB34FLA8zwNL+l6SYvStadvvJ+komRsO9yhJ7/qJEfFQRNzeR7tfDVwTEfdGxLdIivzHRcTNEfGVSHyapBD/qfkeLCLujIg70s+ke4AP4s+A2nOBbJWSFsFLgVvSw1XfBraQvFefBvwl8GngY5J2SfrduUNuQzgpvfxW2oZLJN2Vef7nsMAHlKQXpIf69kjaB7xhoe3NzDo8ACxR91UUnpneP4x7M99/DThxvg37dGL6eMDjPd57OZSpAP+Z+f4AsDjnYz8LOBq4L5PFHwSent7/DkDA5yRtk/R/99nuztfkcZKmlEz6/lb6vOex8GfAcyWtVzKx8jskveH+DKg5F8hWKRERJD22Px0RT8l8HRsRD0TEwxHxroj4AeC/AT/LoR6FGPBpfwbYFRFflfRckkN1lwLfExFPAXaQBPF8z3ETcCOwNCKOB67PbG9m1stngYeBV2ZvTMe8TgGfTG/aDzwps8kzONx8Gbg08/0pHDpqNujjzdlNUshm2/s0kgzvV+dz3UvymizJfA48OSJ+CCAi/jMi3hQRJ5IcdfwT5V+54j6OfE3m9uGJwN8D7wO+N/0MuIWFPwP+FPh34LSIeDLJeGp/BtScC2Sroj8DrpK0FEDS0yW9PP3+HEmnS3oCydjfgyTjvwC+CXxf3ieR9AxJv0ZyWPDy9ObFwGPAHuAJkt5M0oM855vAUklHp4+h9Gf2RsRDkp5PUrSbmeUSEftIhpL9kaRzJR2dDlP4KLAL+Ei66VbgPEnfI+kZJHMisubLwHdKepKkHyIZUzs3LnfQx5vzd8AbJS1PC8vfBTalwwz69U1gWZrtRMR9JEMb3i/pyZKeIOnZks4GkPSzkk5Of/ZBksI172fBTcCvSDpZ0lM5lP8AxwBPJPkMOChpimTsc7adT5N0fOa240g+j2Yk/QDwi/3uvFWPC2SrovcC/wL8q6TvAv8LOCO97yTgH4HvAl8i+c/+pvS+q4HXp7Olj5hQkppIZx7vB75AMpnigrnl5dIxxH8GTJP0Mpyafj/nn4B7gPsl7Up7vN8MvC9t6ztIPtTMzHJLJ8H9FknP5XeATSS9qC9Ox/dCUih/gSSDPsGhQnfO7wFXpEMSfj1z+6dJjoR9EnhfRHxiyMeba/MngXeS9LjeBzybQ0f0+jWXm3slfT79/vUkBevdJEXwx0iGnEAy8W+TpBlgHfCrEfHV9L4rgQ+n7X51l+f6c2Ajyb5/nszkyIj4LvArJJ8rD5JMwF6Xuf/fgbXAzvTxTwR+Pd3uu+ljd5sYaDWj5PPdzMzMmiTthf4qcPQ8EwDNbB7uQTYzMzMzy3CBbGZmZmaW4SEWZmZmZmYZ7kE2MzMzM8votij5WCxZsiSWLVtW1tObmY3UnXfe+UBEnFB2O3pxFptZkw2axaUVyMuWLWN6err3hmZmNSTpa723Kp+z2MyabNAs7jnEQtKHJN0v6Uvz3C9JH5C0Iz097xndtjMzs8E5i83MxifPGOTrgXMXuH8KOC39upTklItmZlas63EWm5mNRc8COSJuBb61wCYXAH8diTuAp0h65gLbm5lZn5zFZmbjU8QqFieRnA5zzq70tiNIulTStKTpPXv2FPDUZmaWchabmRWkiAJZXW7rurhyRFwXEZMRMXnCCZWf3G1mvezdC2efDffcU3ZLzFls1l7O4sIVUSDvApZmrp8M7C7gcc0G19SwqNp+XX893H47XHZZ2S0xZ7FVUdUyqyhV2y9nceGKKJDXAa9PZ1CfBeyLiPsKeFyzwTU1LKq0XxFw9dXw2GNJmzZsKLtFbecstuqpUmYVqUr75SweiTzLvK0FPgt8v6Rdki6R9GZJb043uQXYCewA/hz4pZG11iyPpoZF1fbrtttg377k+wMH4JJL4KGHym1TgzmLrXaqlllFqdp+OYtHoueJQiLioh73B/A/CmuR2bC6hcXOnXDsseW2a1hV269rroH9+w9d37cPrroKrryynPY0nLPYaqdqmVWUqu2Xs3gkihhiYVYt84VF3VVlv+bG3n3pS0lPypwDB+Dmm8ffHjOrpqpkVtGqsl/O4pFygWzNs317M8OiKvs1N/bu1FOT9mS/Nm8ef3vMrJqqkllFq8p+OYtHqucQC7Pa2bat7BaMRhX2q9vYu6mpsltlZlVUhcwahSrsl7N45NyDbGb5eTKImVn5nMUj5wLZzPKrytg7M7M2cxaPnAtkM8uvKmPvzMzazFk8ch6DbGb5VWHsnZlZ2zmLR849yGZmZmZmGS6QzczMzMwyXCCbmZmZmWW4QDYzMzMzy3CBbGZmZmaW4QLZzMzMzCzDBbKZmZmZWYYLZDMzMzOzDBfIZmZmZmYZLpDNzMzMzDJ8qukhzM7Chg2wZQusWAFTUzAxUXarzMzaxVlsZkVzgTyg2VlYtQo2bYL9+2HRIli5EjZudDCbmY2Ls9jMRsFDLAa0YUMSyDMzEJFcbtqU3G5mfdi7F84+G+65p+yWWA05i80K4iw+jAvkAW3ZkvRWZO3fD1u3ltMes9q6/nq4/Xa47LKyW2I15Cw2K4iz+DAukAe0YkVyKC9r0SJYvryc9pjVUgRcfTU89lgSzO72sz45i80K4Cw+ggvkAU1NJePcFi8GKblcuTK5fRizs7B+PaxZk1zOzhbTXrNKuu022Lcv+f7AAbjkEnjooXLbZLXiLDYrgLP4CLkKZEnnStouaYeky7vcf4qkT0naIukuSecV39RqmZhIJoGsXQurVyeXw04KmZtsctFF8O53J5erVjmYrWb6Gcd2zTWHHx/ftw+uumpkTas7Z/GRnMVmXfQ7nthZfISeBbKkCeBaYAo4HbhI0ukdm10B3BQRK4ALgT8puqFVNDEB558PV1yRXA47Y9qTTawR+hnHtn178mafc+AA3HzzyJpWZ87i+TmLzTr0O57YWXyEPD3IZwI7ImJnRDwC3ABc0LFNAE9Ovz8e2F1cE/NpwuEwTzax2ut3HNu2bcnPZL82bx5PW+vHWTwmzmKrtUHGEzuLj5BnHeSTgHsz13cBKzu2uRL4hKRfBhYB53R7IEmXApcCnHLKKf22dV5NWQdzbrLJzMyh2zzZxGql2zi2nTvh2GPLbVczOIvHxFlsteYcLkSeHmR1uS06rl8EXB8RJwPnAR+RdMRjR8R1ETEZEZMnnHBC/62dR1MOh41qsonZ2Hgc2yg5i8fEWWy15hwuRJ4CeRewNHP9ZI48bHcJcBNARHwWOBZYUkQD82jK4bBRTDYxG6txjWNr54L2zuIxcRZbrTmHC5GnQN4MnCbpVEnHkEz8WNexzdeBFwNI+kGSUN5TZEMX0qR1MIuebGI2VuMax9bvBJRmBLmzeIycxVZbVc1hqFUW9yyQI+Ig8BZgI/BlkhnS2yStlvSKdLO3A2+S9AVgLfCGiOg89DcyPhxmY1OjP+7GGmQCSgPOEOUsNks5h8s36IlFapTFGmN2HmZycjKmp6cLe7zZ2eT3s3Vr0lsxNeX/+G0E3v9+eMc74JxzkmOuNn633gove9mhGVTPfObCE1AiYOlS+MY34ElPgo99bCwVm6Q7I2Jy5E80JGex1Y5zuHz95jDULosbcyY9Hw6zkfOpOKuh3wkoPkPUWDmLbaScw9UwyETAmmVxYwpks5Gr2R93Y/U7AcUzus2awzlcDYNMBKxZFrtANsurZn/cjdXvBBSfIcqsOZzD1TDIRMCaZbELZLO8avbHbSmfIcqsOZzD9VWzLM5zJj0zg+SP28zMyuMctjFxD7KZmZmZWYZ7kM3MzGwk5pb927IlOZGMl/2zunAPsjWXF5NvLv9uzSpvdhZWrYKLLoJ3vzu5XLUqud0aoOE57ALZmqtGZ+yxPvl3a1Z5GzbApk3JuSQikstNm7x0cWM0PIddIFszeTH55vLv1qwWtmw5fEU2SK5v3VpOe6xALchhF8hDmp2F9ethzZrk0oeOKsKLyTeXf7fWhbO4elasgEWLDr9t0aLkFORWcy3IYRfIQ/D4qgrzYvKDqcOYMv9urYOzuJqmpmDlSli8GKTkcuXK5HZbgHO4ElwgD8HjqyrMi8kPpg5jyvy7tQ7O4mqamICNG2HtWli9OrncuNGrWPTkHK4EF8hD8PiqCqvZGXsqoS5jyvr53dahJ8aG5iyurokJOP98uOKK5NLFcQ9NzGGoZRa7QB6Cx1dZozRxTFkdemJsaM5ia4wm5jDUMotdIA/B46usUZo2pqwuPTE2NGexNUbTchhqm8UukIfg8VXWKE0bU9bUnhg7grN4OF4BpEKalsNQ2yz2qaaHNDe+6vzzy25JTe3dC698JXz4w7BsWdmtabdt28puQbHm64m58srSmmSj4ywezNwKIJs2JX8uixYlve/+B6MkTcthqG0WuwfZylXDcUlWE03siTErmFcAsZGraRa7QLby1HRc0sjUcJZvpXklE7OevAJIF87iYtU0i10gW3lqOi5pZNrQm+4PHrNK8QogXTiLDRfIVqYmztYdVFt60+v2weMPEWs4rwDSwVlcPSXlsAtkK09NxyWNRBt60+v4wVOnDxGzAXgFkA7O4uopKYdzFciSzpW0XdIOSZfPs82rJd0taZukvyu2mdZINR2XNBJt6E2v2wdPxT5EnMM2Kj7bXYazuFpKzOGeBbKkCeBaYAo4HbhI0ukd25wG/Cbwgoj4IeCtI2irWXO1oTe9bh88FfoQcQ6bjYmzuFpKzOE8PchnAjsiYmdEPALcAFzQsc2bgGsj4kGAiLi/2GaaNVwbetPr9sFTrQ8R57DZODiLq6XEHM5TIJ8E3Ju5viu9Leu5wHMlfUbSHZLO7fZAki6VNC1pes+ePYO12MzqqW4fPNX6ECksh8FZbNZqdcriEnM4z5n01OW26Lh+FHAa8ELgZOA2Sc+LiG8f9kMR1wHXAUxOTnY+hplZdVTrjFaF5TA4i82sJkrM4Tw9yLuApZnrJwO7u2zzjxHxaER8FdhOEtRmZjY857CZ2RjlKZA3A6dJOlXSMcCFwLqObf4BeBGApCUkh/p2FtlQM7MWcw6bmY1RzwI5Ig4CbwE2Al8GboqIbZJWS3pFutlGYK+ku4FPAb8REXtH1WgzszZxDpuZjZciyhl+Njk5GdPT06U8t5nZqEm6MyImy25HL85iM2uyQbPYZ9Izqxuf/tjMrFzO4cZzgWxWNz79sZlZuZzDjecC2axOKnb6YzOz1nEOt4ILZLM6qdDpj83MWsk53AoukM3qpFqnPzYzax/ncCu4QDark2qd/tjMrH2cw62Q51TTZlYV1Tr9sZlZ+ziHW8E9yGZmZmZmGS6QzaxavL6omVn5Wp7FLpDNrFq8vqiZWflansUukK09Wv7fcC14fVGzZnMO14Oz2AWytUjL/xuuBa8vatZszuF6cBa7QLaW8H/D9eD1Rc2ayzlcH85iF8hWjNlZWL8e1qxJLmdny25RB/83XA9eX9RsKJXOYudwfTiLXSDb8GZnYdUquOgiePe7k8tVqyoWzP5vOJ+yxwdu25aEcvZr8+Zy2mJWM5XPYudwPmXnMDiLcYFsBdiwATZtgpmZ5G9oZia5XqmjZ/5vOB+PDzSrrcpnsXM4H+dwJbhAtqFt2XJ4pwAk17duLac9Xfm/4d48PtCs1iqfxc7h3pzDleEC2Ya2YgUsWnT4bYsWwfLl5bTHBuTxgWa15ixuAOdwZbhAtqFNTcHKlbB4MUjJ5cqVye1WIx4faFZrzuIGcA5XxlFlN8Dqb2ICNm5MjgRt3Zr0VkxNJbdbjcw3PvDKK0trkpnl5yxuAOdwZbhAtkJMTMD55ydfVlPbtpXdAjMbkrO45pzDleEhFmZmZmZmGbkKZEnnStouaYekyxfY7lWSQtJkcU00MzNwFpuZjUvPAlnSBHAtMAWcDlwk6fQu2x0H/AqwqehGmpm1nbPYzGx88vQgnwnsiIidEfEIcANwQZft1gDvBbweiZlZ8ZzFZmZjkqdAPgm4N3N9V3rb4yStAJZGxPoC22ZmZoc4i83MxiRPgawutz2+BomkJwBXA2/v+UDSpZKmJU3v2bMnfyvNzMxZbGY2JnkK5F3A0sz1k4HdmevHAc8D/k3SPcBZwLpuk0Mi4rqImIyIyRNOOGHwVpuZtY+z2MxsTPIUyJuB0ySdKukY4EJg3dydEbEvIpZExLKIWAbcAbwiIqZH0mIzs3ZyFpuZjUnPE4VExEFJbwE2AhPAhyJim6TVwHRErFv4EcwWNjubnPlpyxZYscJnfjLrxllso+YsNjsk15n0IuIW4JaO2941z7YvHL5Z1hazs7BqFWzalJx+ftEiWLkyOV2qg9nscM5iGxVnsdnhfCY9K9WGDUkgz8wkp5+fmUmub9hQdsvMzNrDWWx2OBfIfZqdhfXrYc2a5HJ2tuwW1duWLUlvRdb+/bB1azntMbN6cBYXy1lsdrhcQyws4UNQxVuxInkdZ2YO3bZoESxf3v9jefycWTs4i4vnLDY7nAvkPmQPQcHhh6DOP7/cttXV1FTywdb5QTc11d/j+APTrD2cxcVzFpsdzgVyHxY6BOVQHszERBKcGzYkr+Py5YP1Noz7A9M9JGblcRYXz1lsdjgXyH0o8hCUHTIxkQTnMOE5zg9M95CYlctZPBrOYrNDPEmvD3OHoBYvBim5HOQQlBVv7gMzq98PzLyTfjzb26xczuLqGjaL+5l86Sy2UXIPch+KOgRlxet3/FznYbmXvhTOOy9fT4QP75qVy1lcXcNk8Y/8CHzgA/C5z+XrEXYW2yi5QO5TEYegrHj9fGB2Oyz37GfDV76Sb9ycD++alc9ZXE3DZPETnwiPPnqo17jX+GVnsY2SC2RrjLwfmN0mkXz5y0kwZ83XE1HUbG8bDU/aMSvXoFn80ENHbrNQj7CzuNrqnsUukK11uh2We+QROOaY5HLOfD0RPrxbXZ60Y1Yf3bK400I9ws7i6mpCFrtAttaZ77Dcc56TDLPI0xPhw7vV5PVxzeqjWxZPTMDRR8PDD+frEXYWV1MTstirWFjrdJsBf9ZZycSQtWth9erksk7/6VrCp8s1q49uWXz22XDDDc7humtCFrsH2VpnocNy7omoN0/aMauPhbL4ggvKbp0NowlZ7AJ5QHUffN52LoabyZN22sdZXG/O4mZqQha7QB5AEwafmw2i6sWIJ+20i7PY2spZPHoukAfQhMHnZv2qSzHiHqn2cBZbGzmLx8OT9AbQhMHnVl/9nIq1SD6tq1WNs9jK5CxuNvcgD6AJg8+tnsrsOfBpXa1qnMVWFmdx87lAHkATBp9bPZV5SLnJxUh2PN+P/Ehy2113VXNsnx3iLLayOIuL1zmu+qUvhU98orxx1i6QB9CEwedVVvXJB2Uqs+egqcVItidoZubQe+2xx6o7tqJhUuwAAAvvSURBVM8SzuLRcQ4vzFlcrM4e+Sc9KTm77aOPljfO2gXygOo++Lyq6jL5oCxl9hw0tRjp7AnKjiP0pK/qcxYXzzncm7O4WJ05vH//4f+AlJHFnqRnleLJBwvrduapcfYczBUjV1yRXNY5kOd06wnK8qQvaxvncG/O4mL1ymEYfxbnKpAlnStpu6Qdki7vcv/bJN0t6S5Jn5T0rOKbam3gWekLm+s58CmxizPXEzSfqoztcw7buDiHe3MWF6tXDsP4s7jnEAtJE8C1wEuAXcBmSesi4u7MZluAyYg4IOkXgfcCrxlFg63Zmjr5oEg+pFys7Hi++cYglz22zzls4+QczsdZXJzOcdVzY5AfeQQOHCgni/OMQT4T2BEROwEk3QBcADwezBHxqcz2dwAXF9lIa48mTj6wauscz/fDP5zc/sUvVmpsn3PYxsY5bOPWbVz13CoWZY2zzlMgnwTcm7m+C1i5wPaXAF1HKkm6FLgU4JRTTsnZRGuTJk4+sOrr1hN0wQXltaeLwnIYnMW2MOewlaFbDpfZQ5+nQFaX26LrhtLFwCRwdrf7I+I64DqAycnJro9h5sNWVqaKLm9VWA6Ds9h6cw5b2crO4jwF8i5gaeb6ycDuzo0knQP8NnB2RDxcTPPMzManwstbOYfNrDWqkMV5VrHYDJwm6VRJxwAXAuuyG0haAXwQeEVE3F98M83MRq/Cy1s5h82sNaqQxT0L5Ig4CLwF2Ah8GbgpIrZJWi3pFelmfwAsBj4qaaukdfM8nFXQ7CysXw9r1iSX2RMlmLVJVZe3cg63g7PYLFGFLM51Jr2IuAW4peO2d2W+P6fgdtmYVOEwhllVVHl5K+dwszmLzQ6pQhb7THotNddT8fM/D5/5TCUPKZuNXdlnx7J2yfYYv+c9cMcdzmIzqEYW5+pBtmbJ9lRk/zubM3cYw7OXra4Gnf3s5a1sXDp7jI8+OjkpQpaz2OpsmFUoqpDFLpBbKDv4vZuqHFI2G8Swh6q9vJWNQ2cOdxbH4Cy2+ipiyFDZWewhFi3UbfD7nEWL4NnPhjvv9CQRG78iJilVYfazWS/z5fAxxySHlI89Fp7+9ORvwDls4+QcTrgHuYW6DX4/9lh45Sth2zbYsSMZD+dJIjZORU1SWmj2s3uFrSrmm4T01rfC2rWwezfs3AkXX+wctvFxDh/iHuQW6jb4/QUvgFe/Gr7yleRNXNf/+Ky+iupxmCs8snyo2qqmWw6fdRb8+I/D/ffDQw8l2zmHbZycw4e4QG6hucHva9fC6tXJ5caNcNdd5a87aO1V1LqXVZj9bNaLc9iqyDl8SG2GWBR9Tu6yz/Fdtm6D36uw7qC1V1HvvyrMfm4yZ3FxnMNWNc7hQxQRpTzx5ORkTE9P59q26AXUvSB7d35dbNQWKoaa9v6TdGdETJbdjl6cxdXi18TGYb4sbuL7b9AsrkUPcudyONkxMYMM9i768ZqiCf/xWXX1Cl6//6rPWTx6/juwUeuVxX7/JWpRIBc9G7IJsytHpex1B6258hRDfv9Vm7N4PPx3YKPUK4v9/kvUYpJe0bMhmzC70opTxJqP1ltRkz+sPM5iGxXn8Pg4i/OpRQ/y3GzIzsMBg86GLPrxrL6aON6qqjz5qP6cxTYKzuHxchbnU4sCuegxMR5jY3M8BnJ8XAzVn7PYRsE5PF7O4nxqUSBD8WNiPMbGwGMgx8nFUDM4i61ozuHxchbnU5sC2WwUfKhpvFwMmVkn5/D4OYt7q8UkPbNRacLZfszM6sw5bFXkHmRrNR9qMjMrl3PYqsgFso1NVU8p60NNZtYWzmGzfFwg21h4GR8zs3I5h83y8xhkG4vsMj4Rhy/jY2Zmo+ccNsvPBbKNhc/cY2ZWLuewWX4ukG0sfEpZM7NyOYfN8stVIEs6V9J2STskXd7l/idKujG9f5OkZUU31OrNy/iYDc9ZbMNwDpvl13OSnqQJ4FrgJcAuYLOkdRFxd2azS4AHI+I5ki4Efh94zSgabPXkZXzMhuMstmE5h83yy7OKxZnAjojYCSDpBuACIBvKFwBXpt9/DPhjSYqIKLCtVnNexsdsKM5iG5pz2CyfPEMsTgLuzVzfld7WdZuIOAjsA57W+UCSLpU0LWl6z549g7XYzKydnMVmZmOSp0BWl9s6eyPybENEXBcRkxExecIJJ+Rpn5mZJZzFZmZjkqdA3gUszVw/Gdg93zaSjgKOB75VRAPNzAxwFpuZjU2eMcibgdMknQp8A7gQeG3HNuuAnwc+C7wK+NdeY97uvPPOByR9rc/2LgEe6PNn6sj72Rxt2EfwfnbzrIKf21k8Xm3YR/B+Nkkb9hH638+BsrhngRwRByW9BdgITAAfiohtklYD0xGxDvhL4COSdpD0VlyY43H7Pq4naToiJvv9ubrxfjZHG/YRvJ/j4CwerzbsI3g/m6QN+/h/2rufEKvKOIzj3yfEIrA/JEGUYYJCw2wSCdv0ByPEhW4sDKQCCTRo0yoQQmoXVBAI5SKqRWW1qCFsUymGNFagqQnGZFIDki3KTVhGvxbn4JyuOnPGOec998z7fODAufe+i9/vvnce3jnnnnsgXZ91jiATEXuAPQPPPVfZPwc83GxpZmZW5Sw2M0vDd9IzMzMzM6vo2wJ5V9cFJOI+548cegT3mZsc3occegT3OZ/k0CMk6lP+/XgzMzMzsyl9O4JsZmZmZtYqL5DNzMzMzCqGcoEsaa2kE5ImJD17idevlrS7fP2gpKXpq5y7Gn0+I+m4pCOSPpfU9O+qtm6mHivjNkoKSb38iZo6fUp6pJzP7yW9k7rGJtT4zN4uaa+kQ+Xndl0Xdc6FpDcknZF07DKvS9Kr5XtwRNLK1DWmkkMW55DDkEcWO4cvvO4cbkJEDNVG8fuePwLLgIXAd8DIwJingNfK/U3A7q7rbqnPB4Bry/1tfeuzTo/luEXAfmAcWNV13S3N5XLgEHBj+fjmrutuqc9dwLZyfwQ41XXdV9DnvcBK4NhlXl8HfEpxW+fVwMGua+5wvnudxTnkcN0+y3G9zWLn8P/GOIcb2IbxCPLdwEREnIyIv4H3gA0DYzYAb5X7HwJrJClhjU2Ysc+I2BsRf5YPxyluLdsndeYS4AXgReBcyuIaVKfPJ4GdEfE7QEScSVxjE+r0GcB15f71XHwr5KEXEfuZ/vbMG4C3ozAO3CDpljTVJZVDFueQw5BHFjuHpziHGzCMC+RbgV8qjyfL5y45JiL+Ac4CNyWprjl1+qzaQvHfUp/M2KOku4AlEfFJysIaVmcuVwArJB2QNC5pbbLqmlOnzx3AZkmTFDe0eDpNaUnN9m+3r3LI4hxyGPLIYufwlB04h+es1p30ErvU0YfB36KrM2bY1e5B0mZgFXBfqxU1b9oeJV0FvAI8kaqgltSZywUUp/fupzgC9aWk0Yj4o+XamlSnz0eBNyPiJUn3UNz2eDQi/m2/vGTmQ/7UkUMW55DDkEcWO4enOIcbMIxHkCeBJZXHt3Hx6YELYyQtoDiFMN2h+GFUp08kPQhsB9ZHxF+JamvKTD0uAkaBfZJOUXyPaKyHF4fU/cx+HBHnI+In4ARFUPdJnT63AO8DRMRXwDXA4iTVpVPrb3ceyCGLc8hhyCOLncNTnMMNGMYF8jfAckl3SFpIceHH2MCYMeDxcn8j8EWU39rukRn7LE95vU4Ryn38rtS0PUbE2YhYHBFLI2Ipxff71kfEt92Ue8XqfGY/orjYB0mLKU71nUxa5dzV6fNnYA2ApDspgvm3pFW2bwx4rLyKejVwNiJOd11UC3LI4hxyGPLIYufwFOdwE1JcjTjbjeLqxB8ortTcXj73PMUfLBST/QEwAXwNLOu65pb6/Az4FThcbmNd19x0jwNj99GzK6dnMZcCXgaOA0eBTV3X3FKfI8ABiiurDwMPdV3zFfT4LnAaOE9xlGILsBXYWpnLneV7cLSvn9mG5rv3WZxDDtfpc2BsL7PYOewcbnLzrabNzMzMzCqG8SsWZmZmZmad8QLZzMzMzKzCC2QzMzMzswovkM3MzMzMKrxANjMzMzOr8ALZzMzMzKzCC2QzMzMzs4r/AJGnCcemUNWrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as pl\n",
    "import numpy as np\n",
    "\n",
    "def train(data,classes,weights,whichdim):\n",
    "\n",
    "    error = np.zeros(10)\n",
    "    for value in range(0,10,1):\n",
    "        val = float(value)/10                                ### try all values on current dimension in steps of 0.1\n",
    "        classn = np.where(data[whichdim,:]<val,-1,1)         ### all data points below this line are -1\n",
    "        ind = np.where(classes!=classn)                      ### all misclassified data points\n",
    "        error[value] = np.sum(weights[ind])                  ### sum up weighted errors for line at this value\n",
    "    return whichdim,float(np.argmin(error))/10,1-whichdim    ### return least error line\n",
    "\n",
    "def classify(data,classes,dim,value):\n",
    "    dim = int(dim)# modify here\n",
    "    # modify here \n",
    "    classn = np.where(data[dim,:]<value,-1,1)\n",
    "    ind = np.where(classes!=classn,1,0)\n",
    "    return classn, ind\n",
    "\n",
    "def boost(data,classes,testdata,testclasses):\n",
    "    T = 20\n",
    "    N = np.shape(data)[1]\n",
    "    ndim = np.shape(data)[0]\n",
    "    classifiers = np.zeros((2,T))         ### a 2 x 20 array; a classifier is learned on each of 20 boosting iterations\n",
    "    whichdim = 0                          ### initial choice of x or y dimension for classifier\n",
    "\n",
    "    w = np.ones((N,T+1),dtype=float)/N    ### initialise each of N examples to have uniform weight\n",
    "    index = np.ones((N,T+1))              ### same shape, used for class of each example\n",
    "    e = np.zeros(T)                       ### error store for each iteration\n",
    "    alpha = np.zeros(T+1)                 ### for the classifier weight on each iteration\n",
    "\n",
    "    err = np.zeros((2,T+1))               ### for classification error for each example on each iteration\n",
    "\n",
    "    poutput = np.zeros((T+1,N))\n",
    "    ptoutput = np.zeros((T+1,N))\n",
    "    po = np.zeros(T+1)\n",
    "    pto = np.zeros(T+1)\n",
    "    f = pl.figure(figsize=(14,8))\n",
    "    for t in range(T):\n",
    "        classifiers[0,t],classifiers[1,t],whichdim = train(data,classes,w[:,t],whichdim)\n",
    "        outputs,errors = classify(data,classes,classifiers[0,t],classifiers[1,t])\n",
    "        toutputs,terrors = classify(testdata,testclasses,classifiers[0,t],classifiers[1,t])\n",
    "        which = np.where(outputs<=0)\n",
    "        which2 = np.where(outputs>0)\n",
    "        \n",
    "        ax=f.add_subplot(5,4,t+1)\n",
    "        ax.plot(data[0,which],data[1,which],'bo',ms=3)\n",
    "        ax.plot(data[0,which2],data[1,which2],'r^',ms=3)\n",
    "        dummy1=np.linspace(0., 1., num=11)\n",
    "        dummy0=np.zeros(11)\n",
    "        dummy2=np.add(dummy0,classifiers[1,t])\n",
    "        \n",
    "        if  classifiers[0,t] == 0:\n",
    "            ax.plot(dummy2,dummy1,'c-')\n",
    "        else:\n",
    "            ax.plot(dummy1,dummy2,'c-')\n",
    "        cur_title = 'iteration ' + str(t+1)\n",
    "        ax.set_title(cur_title)\n",
    "        \n",
    "        index[:,t] = errors\n",
    "        e[t] = np.sum(w[:,t]*index[:,t])/np.sum(w[:,t])     ### total error of classifiers on this iteration\n",
    "\n",
    "        if t>0 and (e[t]==0 or e[t]>=0.5):                  ### Halt: we no longer have a weak learner on iteration t\n",
    "            T=t\n",
    "            alpha = alpha[:t]\n",
    "            index = index[:,:t]\n",
    "            w = w[:,:t]\n",
    "            break\n",
    "\n",
    "        alpha[t] = np.log((1-e[t])/e[t])                   ### version in lectures prefaced by 1/2 to ease derivation\n",
    "        w[:,t+1] = w[:,t]* np.exp(alpha[t]*index[:,t])     ### reweight all examples\n",
    "        w[:,t+1] = w[:,t+1]/np.sum(w[:,t+1])               ### normalise to keep constant weight\n",
    "\n",
    "        outputs = np.zeros((N,t))\n",
    "        toutputs = np.zeros((N,t))\n",
    "        for i in range(t):\n",
    "            outputs[:,i],errors  = classify(data,classes,classifiers[0,i],classifiers[1,i])\n",
    "            toutputs[:,i],terrors  = classify(testdata,testclasses,classifiers[0,i],classifiers[1,i])\n",
    "\n",
    "        for n in range(N):\n",
    "            poutput[t,n] = np.sum(alpha[:t]*outputs[n,:])/sum(alpha)\n",
    "            ptoutput[t,n] = np.sum(alpha[:t]*toutputs[n,:])/sum(alpha)\n",
    "        poutput[t,:] = np.where(poutput[t,:]>0,1,-1)\n",
    "        ptoutput[t,:] = np.where(ptoutput[t,:]>0,1,-1)\n",
    "        po[t] = np.shape(np.where(poutput[t,:]!=classes))[1]\n",
    "        pto[t] = np.shape(np.where(ptoutput[t,:]!=testclasses))[1]\n",
    "    pl.tight_layout()\n",
    "\n",
    "    outputs = np.zeros((N,np.shape(w)[1]))\n",
    "    for t in range(T):\n",
    "        outputs[:,t],errors  = classify(data,classes,classifiers[0,t],classifiers[1,t])\n",
    "\n",
    "    output = np.zeros(N)\n",
    "    for n in range(N):\n",
    "        output[n] = np.sum(alpha*outputs[n,:])/np.sum(alpha)\n",
    "    pl.figure()\n",
    "    f = pl.figure(figsize=(10,6))\n",
    "    ax=f.add_subplot(2,2,1)\n",
    "    classes = np.where(((data[0,:]>0.4) & (data[1,:]>0.4)),1,-1)             ### positive labels in top-right corner \n",
    "    which = np.where(classes==-1)\n",
    "    which2 = np.where(classes==1)\n",
    "    ax.plot(data[0,which],data[1,which],'bo',ms=5)\n",
    "    ax.plot(data[0,which2],data[1,which2],'r^',ms=5)\n",
    "    ax.set_title('Training Data')\n",
    "\n",
    "    ax=f.add_subplot(2,2,2)\n",
    "    which = np.where(output<=0)\n",
    "    which2 = np.where(output>0)\n",
    "    ax.plot(data[0,which],data[1,which],'bo',ms=5)\n",
    "    ax.plot(data[0,which2],data[1,which2],'r^',ms=5)\n",
    "    ax.set_title('Output on training data')\n",
    "\n",
    "    outputs = np.zeros((N,np.shape(w)[1]))\n",
    "    for t in range(T):\n",
    "        outputs[:,t],errors  = classify(testdata,testclasses,classifiers[0,t],classifiers[1,t])\n",
    "\n",
    "    output = np.zeros(N)\n",
    "    for n in range(N):\n",
    "        output[n] = np.sum(alpha*outputs[n,:])/np.sum(alpha)\n",
    "    which = np.where(output<=0)\n",
    "    which2 = np.where(output>0)\n",
    "    ax=f.add_subplot(2,2,4)\n",
    "    ax.set_title('Output on test data')\n",
    "    ax.plot(testdata[0,which],testdata[1,which],'bo',ms=5)\n",
    "    ax.plot(testdata[0,which2],testdata[1,which2],'r^',ms=5)\n",
    "\n",
    "    ax=f.add_subplot(2,2,3)\n",
    "    ax.set_title('Test Data')\n",
    "    which = np.where(testclasses==-1)\n",
    "    which2 = np.where(testclasses==1)\n",
    "    ax.plot(testdata[0,which],testdata[1,which],'bo',ms=5)\n",
    "    ax.plot(testdata[0,which2],testdata[1,which2],'r^',ms=5)\n",
    "    pl.tight_layout()\n",
    "\n",
    "    pl.figure()\n",
    "    pl.plot(np.arange(T),po[:T]/N,'k-',np.arange(T),pto[:T]/N,'k--')\n",
    "    pl.legend(('Training error','Test error'))\n",
    "    pl.xlabel('Iterations')\n",
    "    pl.ylabel('Error')\n",
    "    return output\n",
    "\n",
    "def test_boost():\n",
    "    pl.ion()                               ### interactive plotting on\n",
    "    ndata = 50\n",
    "    data = np.random.rand(2,ndata)         ### uniformly distributed random 2D data\n",
    "    classes = np.where(((data[0,:]>0.4) & (data[1,:]>0.4)),1,-1)             ### positive labels in top-right corner \n",
    "    testdata = np.random.rand(2,ndata)\n",
    "    testclasses = np.where(((testdata[0,:]>0.4) & (testdata[1,:]>0.4)),1,-1) ### positive labels in top-right corner \n",
    "    boost(data,classes,testdata,testclasses)\n",
    "\n",
    "\n",
    "test_boost()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Discussion of boosting output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "In the plots above we can see ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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